Pub Date : 2024-01-30DOI: 10.3103/s1060992x23070093
A. M. Ishkhanyan, T. A. Shahverdyan, A. M. Ghazaryan
Abstract
We present a novel time-dependent two-state model that describes a constant-amplitude level-crossing field configuration, where the frequency detuning varies within a finite interval. A distinctive feature of this configuration is that the resonance crossing always occurs asymmetrically in time, making it an asymmetric version of the second Demkov-Kunike model. The general solution of the problem is expressed in terms of two independent irreducible linear combinations of the Gauss hypergeometric functions. We analyze the asymptotes of the solution in terms of corresponding quasi-energies and calculate the final transition probability in the case when the system starts from the first quasi-energy state.
{"title":"Asymmetric Version of the Second Demkov–Kunike Level-Crossing Model","authors":"A. M. Ishkhanyan, T. A. Shahverdyan, A. M. Ghazaryan","doi":"10.3103/s1060992x23070093","DOIUrl":"https://doi.org/10.3103/s1060992x23070093","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>We present a novel time-dependent two-state model that describes a constant-amplitude level-crossing field configuration, where the frequency detuning varies within a finite interval. A distinctive feature of this configuration is that the resonance crossing always occurs asymmetrically in time, making it an asymmetric version of the second Demkov-Kunike model. The general solution of the problem is expressed in terms of two independent irreducible linear combinations of the Gauss hypergeometric functions. We analyze the asymptotes of the solution in terms of corresponding quasi-energies and calculate the final transition probability in the case when the system starts from the first quasi-energy state.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140886177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.3103/s1060992x23070214
Lusine Tsarukyan, Anahit Badalyan, Lusine Aloyan, Yeva Dalyan, Rafael Drampyan
Abstract
The nonuniform 2D photovoltaic fields generated near the surface of a photorefractive Fe-doped lithium niobate (LN:Fe) crystal by a nondiffracting optical Bessel beam with concentric ring structures and 532 nm wavelength are used for the trapping of DNA molecules in NaCl buffer on the crystal surface. The simultaneous observation of the long-living Bessel-like refractive lattice recorded in the LN:Fe crystal and the trapped DNA molecules on the crystal surface was performed by an optical phase microscope operating in the transmission mode. With this approach, the DNA molecules are registered as refractive index nonuniformities on the Bessel lattice refractive index pattern. Observations show that DNA molecules are immobilized and trapped at the borderlines of the concentric rings of the refractive lattice recorded by the Bessel beam. The formation of neutral molecular clusters of DNA by Na+ counterions with a nearly globular shape and cluster average size of ~4 μm is revealed. A physical model is developed for the analysis of the electric forces map and explanation of the experimental results. The photovoltaic strategy of trapping and manipulation of micro- and nanoparticles on the crystal surface is promising for the elaboration of the lab-on-a-chip devices operating in an autonomous regime with applications in photonics, micro/nano-electronics and biotechnology.
{"title":"Photovoltaic Tweezers Based on Optical Holography: Application to 2D Trapping of DNA Molecules on a Lithium Niobate Crystal","authors":"Lusine Tsarukyan, Anahit Badalyan, Lusine Aloyan, Yeva Dalyan, Rafael Drampyan","doi":"10.3103/s1060992x23070214","DOIUrl":"https://doi.org/10.3103/s1060992x23070214","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The nonuniform 2D photovoltaic fields generated near the surface of a photorefractive Fe-doped lithium niobate (LN:Fe) crystal by a nondiffracting optical Bessel beam with concentric ring structures and 532 nm wavelength are used for the trapping of DNA molecules in NaCl buffer on the crystal surface. The simultaneous observation of the long-living Bessel-like refractive lattice recorded in the LN:Fe crystal and the trapped DNA molecules on the crystal surface was performed by an optical phase microscope operating in the transmission mode. With this approach, the DNA molecules are registered as refractive index nonuniformities on the Bessel lattice refractive index pattern. Observations show that DNA molecules are immobilized and trapped at the borderlines of the concentric rings of the refractive lattice recorded by the Bessel beam. The formation of neutral molecular clusters of DNA by Na<sup>+</sup> counterions with a nearly globular shape and cluster average size of ~4 μm is revealed. A physical model is developed for the analysis of the electric forces map and explanation of the experimental results. The photovoltaic strategy of trapping and manipulation of micro- and nanoparticles on the crystal surface is promising for the elaboration of the lab-on-a-chip devices operating in an autonomous regime with applications in photonics, micro/nano-electronics and biotechnology.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140885994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.3103/s1060992x2307010x
B. V. Kryzhanovsky, V. I. Egorov
Abstract
The possibility of the maximum-likelihood algorithm-based deep learning of an optical neural network is considered. Using the optimization of thermodynamic parameters of the network, the algorithm can fail when the network undergoes a phase transition caused by changes of network weights in learning. The approach based on Schraudolph–Kamenetsky [1] and Karandashev–Malsagov [2] algorithms is used in computer simulation. Both algorithms allow the free energy of the system on a planar graph to be computed exactly. The restrictions on the number of negative connections are determined that secure the stability of the system, the absence of the phase transition and unrestrained use of the maximum-likelihood algorithm.
{"title":"Stability of an Optical Neural Network Trained by the Maximum-Likelihood Algorithm","authors":"B. V. Kryzhanovsky, V. I. Egorov","doi":"10.3103/s1060992x2307010x","DOIUrl":"https://doi.org/10.3103/s1060992x2307010x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The possibility of the maximum-likelihood algorithm-based deep learning of an optical neural network is considered. Using the optimization of thermodynamic parameters of the network, the algorithm can fail when the network undergoes a phase transition caused by changes of network weights in learning. The approach based on Schraudolph–Kamenetsky [1] and Karandashev–Malsagov [2] algorithms is used in computer simulation. Both algorithms allow the free energy of the system on a planar graph to be computed exactly. The restrictions on the number of negative connections are determined that secure the stability of the system, the absence of the phase transition and unrestrained use of the maximum-likelihood algorithm.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140885997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.3103/s1060992x23070147
Iris Mowgood, Serafim Teknowijoyo, Sara Chahid, Armen Gulian
Abstract
Based on time-dependent Ginzburg-Landau system of equations, Éliashberg’s kinetic equations and finite element modeling, we analyze phonon emission by the phase-slip centers in superconducting filaments. Our results show that in the dissipative regime with these centers, thin superconducting filaments can be effective in originating not only positive but also negative thermal fluxes, i.e., they both generate and absorb phonons. In a stationary oscillatory regime, at a given moment of time, this generation and absorption of phonons reveals itself as positive and negative spectrum of phonons at different spectral ranges. Moreover, at a given spectral range, the emission reverses its sign during the period of oscillation. This fact is associated with the reciprocation of the energy emission and absorption at different spectral intervals during the oscillation period of the phase-slip center. The integral value of energy over the whole spectral range is time-dependent, being positive for some part of the period and negative for the rest of it. Its time integral over the period reveals a positive value, which corresponds to the total energy released in this dissipative state of superconducting filament. In a simple case, when the filament is embedded in a thermal heat bath (substrates typically play that role), this energy dissipates, elevating locally the temperature of filament’s environment. However, in a more sophisticated design, the positive and negative fluxes may become separated. This can be achieved by using the thermal diode effect (the Kapitza boundaries can play the role of such diodes). Such a separation may yield to the net cooling of some part of the filament environment, while the other part will serve as a heat sink. Thus, with an appropriate design of their thermal surroundings, the phase-slip centers can serve as effective solid-state cooling engines. They may be effective for reducing further the cryostat cold finger temperature; for example, from 1 K to sub-K temperatures.
摘要基于时间相关的金兹堡-朗道方程组、埃利亚什伯格动力学方程和有限元建模，我们分析了超导丝中相滑中心的声子发射。我们的研究结果表明，在有这些中心的耗散状态下，细超导丝不仅能有效地产生正的热通量，也能有效地产生负的热通量，也就是说，它们既能产生声子，也能吸收声子。在静态振荡机制中，在给定的时间内，声子的产生和吸收表现为不同光谱范围的正负声子谱。此外，在给定的光谱范围内，声子的发射在振荡期间会反转其符号。这与相位滑动中心振荡期间不同光谱区间的能量发射和吸收互为因果有关。整个光谱范围内的能量积分值与时间有关，在振荡周期的某些时段为正值，其余时段为负值。它在整个周期内的时间积分为正值，相当于超导丝在这种耗散状态下释放的总能量。在简单的情况下，当超导丝嵌入热浴盆中时（基板通常起到这种作用），这种能量就会耗散，使超导丝所处环境的局部温度升高。然而，在更复杂的设计中，正负通量可能会分离。这可以通过热二极管效应来实现（卡皮查边界可以起到这种二极管的作用）。这种分离可以使灯丝环境的某些部分实现净冷却，而另一部分则充当散热器。因此，只要对其热环境进行适当设计，相位滑动中心就能成为有效的固态冷却引擎。它们可以有效地进一步降低低温恒温器的冷指温度，例如从 1 K 降到亚 K 温度。
{"title":"Phase-Slip Centers as Cooling Engines","authors":"Iris Mowgood, Serafim Teknowijoyo, Sara Chahid, Armen Gulian","doi":"10.3103/s1060992x23070147","DOIUrl":"https://doi.org/10.3103/s1060992x23070147","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Based on time-dependent Ginzburg-Landau system of equations, Éliashberg’s kinetic equations and finite element modeling, we analyze phonon emission by the phase-slip centers in superconducting filaments. Our results show that in the dissipative regime with these centers, thin superconducting filaments can be effective in originating not only positive but also negative thermal fluxes, i.e., they both generate and absorb phonons. In a stationary oscillatory regime, at a given moment of time, this generation and absorption of phonons reveals itself as positive and negative spectrum of phonons at different spectral ranges. Moreover, at a given spectral range, the emission reverses its sign during the period of oscillation. This fact is associated with the reciprocation of the energy emission and absorption at different spectral intervals during the oscillation period of the phase-slip center. The integral value of energy over the whole spectral range is time-dependent, being positive for some part of the period and negative for the rest of it. Its time integral over the period reveals a positive value, which corresponds to the total energy released in this dissipative state of superconducting filament. In a simple case, when the filament is embedded in a thermal heat bath (substrates typically play that role), this energy dissipates, elevating locally the temperature of filament’s environment. However, in a more sophisticated design, the positive and negative fluxes may become separated. This can be achieved by using the thermal diode effect (the Kapitza boundaries can play the role of such diodes). Such a separation may yield to the net cooling of some part of the filament environment, while the other part will serve as a heat sink. Thus, with an appropriate design of their thermal surroundings, the phase-slip centers can serve as effective solid-state cooling engines. They may be effective for reducing further the cryostat cold finger temperature; for example, from 1 K to sub-K temperatures.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139648843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.3103/s1060992x23070068
G. G. Demirkhanyan, R. B. Kostanyan
Abstract—
The possibilities of LaF3–Er3+crystal to obtain cascade lasing with CW pumping at 0.52 μm wavelength are considered. The conditions for the formation of inverse populations between Stark levels of neighboring manifolds are determined. It is shown that, at 100 K and CW pump intensity ({{J}_{p}} geqslant 350,,{{text{W}} mathord{left/ {vphantom {{text{W}} {{text{c}}{{{text{m}}}^{2}}}}} right. kern-0em} {{text{c}}{{{text{m}}}^{2}}}}), it is possible to obtain simultaneously laser radiation at 3.21 and 2.88 μm wavelengths.
{"title":"LaF3–Er3+ Crystal as Materials for MIR-Lasing Operating","authors":"G. G. Demirkhanyan, R. B. Kostanyan","doi":"10.3103/s1060992x23070068","DOIUrl":"https://doi.org/10.3103/s1060992x23070068","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract—</h3><p>The possibilities of LaF<sub>3</sub>–Er<sup>3+</sup>crystal to obtain cascade lasing with CW pumping at 0.52 μm wavelength are considered. The conditions for the formation of inverse populations between Stark levels of neighboring manifolds are determined. It is shown that, at 100 K and CW pump intensity <span>({{J}_{p}} geqslant 350,,{{text{W}} mathord{left/ {vphantom {{text{W}} {{text{c}}{{{text{m}}}^{2}}}}} right. kern-0em} {{text{c}}{{{text{m}}}^{2}}}})</span>, it is possible to obtain simultaneously laser radiation at 3.21 and 2.88 μm wavelengths.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140886140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.3103/s1060992x23070135
R. Momier, A. Sargsyan, A. Tonoyan, C. Leroy, D. Sarkisyan
Abstract
In strong magnetic fields (0.1–6 kG), many atomic lines closely spaced in frequency appear in the absorption spectrum of alkali metal vapors. Due to the small frequency interval between them and the Doppler broadening of the atomic lines, they are overlapped. For spectral separation and study of individual atomic lines, it is necessary to ensure their spectral narrowing. It is shown that this can be done using the saturated absorption method in an atomic vapor contained in a 30 μm-thick cell filled with Rb vapor. All 10 atomic transitions of Rb D1 line are spectrally very well resolved in the second derivative of the saturated absorption spectrum. Complete resolution of atomic transitions makes this method useful for the determination of a wide range of magnetic fields. The theoretical curves describe the experimental results very well.
{"title":"Micrometric-Thin Cell Filled with Rb Vapor for High-Resolution Atomic Spectroscopy","authors":"R. Momier, A. Sargsyan, A. Tonoyan, C. Leroy, D. Sarkisyan","doi":"10.3103/s1060992x23070135","DOIUrl":"https://doi.org/10.3103/s1060992x23070135","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In strong magnetic fields (0.1–6 kG), many atomic lines closely spaced in frequency appear in the absorption spectrum of alkali metal vapors. Due to the small frequency interval between them and the Doppler broadening of the atomic lines, they are overlapped. For spectral separation and study of individual atomic lines, it is necessary to ensure their spectral narrowing. It is shown that this can be done using the saturated absorption method in an atomic vapor contained in a 30 μm-thick cell filled with Rb vapor. All 10 atomic transitions of Rb D<sub>1</sub> line are spectrally very well resolved in the second derivative of the saturated absorption spectrum. Complete resolution of atomic transitions makes this method useful for the determination of a wide range of magnetic fields. The theoretical curves describe the experimental results very well.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139648841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.3103/s1060992x23070032
S. G. Arutunian, M. A. Aginian, E. G. Lazareva, M. Chung
Abstract
The paper discusses the representation of the electromagnetic field of an arbitrarily moving charged particle by means of electric field lines. Expressions for the field line equations are derived on the basis of exact Lienar-Wichert field formulas. Parameterization of field lines by means of light signals (dots) emitted at delayed moments of time allows us to avoid the problem of solving the retardation equation. The resulting nonlinear equations are linearized using the Lorentz transformation applied to the emission rate of these light dots in the particle’s rest frame. These linear equations coincide with the Thomas precession equation, which allows us to state that field lines can be thought of as comprised of light dots that were emitted isotropically in the particle’s rest frame at speed (c). The exact solution of the equations is found in the case when the ratio of the trajectory torsion to the product of the trajectory curvature by the Lorentz factor of the particle is a constant value for the trajectory. The class of such fields in particular includes all flat trajectories. Illustrations of field lines are given for two applications of practical interest – the motion of a charged particle in the field of a plane monochromatic linearly polarized wave and for a helical undulator. In addition, it is shown that the developed mathematical apparatus admits consideration of the superluminal motion of the charge. Exact solutions and illustrations of lines for the superluminal motion of a particle along a circle (superluminal synchrotron radiation) are given.
{"title":"Representation of the Electromagnetic Field of an Arbitrarily Moving Charged Particle by Electric Field Lines","authors":"S. G. Arutunian, M. A. Aginian, E. G. Lazareva, M. Chung","doi":"10.3103/s1060992x23070032","DOIUrl":"https://doi.org/10.3103/s1060992x23070032","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper discusses the representation of the electromagnetic field of an arbitrarily moving charged particle by means of electric field lines. Expressions for the field line equations are derived on the basis of exact Lienar-Wichert field formulas. Parameterization of field lines by means of light signals (dots) emitted at delayed moments of time allows us to avoid the problem of solving the retardation equation. The resulting nonlinear equations are linearized using the Lorentz transformation applied to the emission rate of these light dots in the particle’s rest frame. These linear equations coincide with the Thomas precession equation, which allows us to state that field lines can be thought of as comprised of light dots that were emitted isotropically in the particle’s rest frame at speed <span>(c)</span>. The exact solution of the equations is found in the case when the ratio of the trajectory torsion to the product of the trajectory curvature by the Lorentz factor of the particle is a constant value for the trajectory. The class of such fields in particular includes all flat trajectories. Illustrations of field lines are given for two applications of practical interest – the motion of a charged particle in the field of a plane monochromatic linearly polarized wave and for a helical undulator. In addition, it is shown that the developed mathematical apparatus admits consideration of the superluminal motion of the charge. Exact solutions and illustrations of lines for the superluminal motion of a particle along a circle (superluminal synchrotron radiation) are given.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139649445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Deploying AI models on resource-constrained devices is indeed a challenging task. It requires models to have a small parameter while maintaining high performance. Achieving a balance between model size and performance is essential to ensuring the efficient and effective deployment of AI models in such environments. Knowledge distillation (KD) is an important model compression technique that aims to have a small model learn from a larger model by leveraging the high-performance features of the larger model to enhance the performance of the smaller model, ultimately achieving or surpassing the performance of the larger models. This paper presents a pipeline-based knowledge distillation method that improves model performance through non-linear feature alignment (FA) after the feature extraction stage. We conducted experiments on both single-teacher distillation and multi-teacher distillation and through extensive experimentation, we demonstrated that our method can improve the accuracy of knowledge distillation on the existing KD loss function and further improve the performance of small models.
{"title":"Enhancement of Knowledge Distillation via Non-Linear Feature Alignment","authors":"Jiangxiao Zhang, Feng Gao, Lina Huo, Hongliang Wang, Ying Dang","doi":"10.3103/s1060992x23040136","DOIUrl":"https://doi.org/10.3103/s1060992x23040136","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Deploying AI models on resource-constrained devices is indeed a challenging task. It requires models to have a small parameter while maintaining high performance. Achieving a balance between model size and performance is essential to ensuring the efficient and effective deployment of AI models in such environments. Knowledge distillation (KD) is an important model compression technique that aims to have a small model learn from a larger model by leveraging the high-performance features of the larger model to enhance the performance of the smaller model, ultimately achieving or surpassing the performance of the larger models. This paper presents a pipeline-based knowledge distillation method that improves model performance through non-linear feature alignment (FA) after the feature extraction stage. We conducted experiments on both single-teacher distillation and multi-teacher distillation and through extensive experimentation, we demonstrated that our method can improve the accuracy of knowledge distillation on the existing KD loss function and further improve the performance of small models.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139029221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-22DOI: 10.3103/s1060992x23040069
O. Angelsky, A. Bekshaev, C. Zenkova, D. Ivanskyi, P. Maksymyak, V. Kryvetsky, Zhebo Chen
Abstract
The paper offers a short review of the recent works associated with the use of luminescent carbon nanoparticles for the studies of structurally inhomogeneous optical fields carrying a diagnostic information on inhomogeneous material objects. Methods for obtaining nanoparticles with various specially assigned optical and electrical properties, necessary for research and diagnostic tasks, are analyzed. It is shown that the light-induced motion of nanoparticles suspended in the optical field enable detection and localization of the points of intensity minima and phase singularities. Optically-driven nanoparticles can serve as highly-sensitive probes of the object surface inhomogeneities, realizing a contactless version of the atomic-force profilometry. In many cases, the use of nanoparticles makes it possible to circumvent the spatial-resolution limitations of optical systems dictated by the classical wave-optics concepts (Rayleigh limit).
{"title":"Application of the Luminescent Carbon Nanoparticles for Optical Diagnostics of Structure-Inhomogeneous Objects at the Micro- and Nanoscales","authors":"O. Angelsky, A. Bekshaev, C. Zenkova, D. Ivanskyi, P. Maksymyak, V. Kryvetsky, Zhebo Chen","doi":"10.3103/s1060992x23040069","DOIUrl":"https://doi.org/10.3103/s1060992x23040069","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper offers a short review of the recent works associated with the use of luminescent carbon nanoparticles for the studies of structurally inhomogeneous optical fields carrying a diagnostic information on inhomogeneous material objects. Methods for obtaining nanoparticles with various specially assigned optical and electrical properties, necessary for research and diagnostic tasks, are analyzed. It is shown that the light-induced motion of nanoparticles suspended in the optical field enable detection and localization of the points of intensity minima and phase singularities. Optically-driven nanoparticles can serve as highly-sensitive probes of the object surface inhomogeneities, realizing a contactless version of the atomic-force profilometry. In many cases, the use of nanoparticles makes it possible to circumvent the spatial-resolution limitations of optical systems dictated by the classical wave-optics concepts (Rayleigh limit).</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139029220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-22DOI: 10.3103/s1060992x23040124
S. Ye, R. Bohush, H. Chen, S. Ihnatsyeva, S. V. Ablameyko
Abstract
A new image set, augmentation method and fine in-learning adjustment of convolutional neural networks (CNN) are proposed to increase the accuracy of CNN-based person re-identification. Unlike other known sets, we have used many video frames from external and internal surveillance systems shot at all seasons of the year to make up our PolReID1077 set of person images. The PolReID1077-forming samples are subjected to the cyclic shift, chroma subsampling, and replacement of a fragment by a reduced copy of another sample to get a wider range of images. The learning set generating technique is used to train a CNN. The training is carried out in two stages. The first stage is pre-training using the augmented data. At the second stage the original images are used to carry out fine-tuning of CNN weight coefficients to reduce in-learning losses and increase re-identification efficiency. The approach doesn’t allow the CNN to remember learning sets and decreases the chances of overfitting. Different augmentation methods, data sets and learning techniques are used in the experiments.
{"title":"Data Augmentation and Fine Tuning of Convolutional Neural Network during Training for Person Re-Identification in Video Surveillance Systems","authors":"S. Ye, R. Bohush, H. Chen, S. Ihnatsyeva, S. V. Ablameyko","doi":"10.3103/s1060992x23040124","DOIUrl":"https://doi.org/10.3103/s1060992x23040124","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>A new image set, augmentation method and fine in-learning adjustment of convolutional neural networks (CNN) are proposed to increase the accuracy of CNN-based person re-identification. Unlike other known sets, we have used many video frames from external and internal surveillance systems shot at all seasons of the year to make up our PolReID1077 set of person images. The PolReID1077-forming samples are subjected to the cyclic shift, chroma subsampling, and replacement of a fragment by a reduced copy of another sample to get a wider range of images. The learning set generating technique is used to train a CNN. The training is carried out in two stages. The first stage is pre-training using the augmented data. At the second stage the original images are used to carry out fine-tuning of CNN weight coefficients to reduce in-learning losses and increase re-identification efficiency. The approach doesn’t allow the CNN to remember learning sets and decreases the chances of overfitting. Different augmentation methods, data sets and learning techniques are used in the experiments.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139029213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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