Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9908624
Kiran Kumar Godugu, Suseela Vappangi
With the aid of cooperative spectrum sensing (CSS), the performance characteristics of non-cooperative cognitive radio (CR) nodes can be substantially improved under the scenario of shadowing, fading, uncertainties in the channel, etc. Predominantly, the CSS scheme decreases the probabilities of miss-detection and false alarm considerably. The CSS is also mapped into multiple primary users (PU) detection schemes using orthogonal frequency division multiplexing (OFDM) technique. In this paper, we introduce a novel multi-band joint detection scheme known as wide-band spectrum sensing (WSS) in cognitive radio networks (CRN) that jointly detects various available channels rather than one frequency at a time. The proposed WSS not only enhances the dynamic spectrum utilization but also lowers the interference to the PUs. Furthermore, by lowering the PU’s interference over AWGN channel, the optimal solutions for WSS under non-cooperative and cooperative systems are investigated. This work formulates the mathematical framework for measuring miss-detection as well as total error probability (TEP). The derived analytical expressions are validated through MATLAB-based simulations. From the simulated results, it can be deduced that the proposed WSS scheme significantly enhances the performance of the system when compared with the conventional CSS schemes.
{"title":"Performance Analysis of Wideband Spectrum Sensing (WSS) in Cognitive Radio Networks (CRN) over Erroneous Sensing and Reporting Channels","authors":"Kiran Kumar Godugu, Suseela Vappangi","doi":"10.1109/ASIANCON55314.2022.9908624","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908624","url":null,"abstract":"With the aid of cooperative spectrum sensing (CSS), the performance characteristics of non-cooperative cognitive radio (CR) nodes can be substantially improved under the scenario of shadowing, fading, uncertainties in the channel, etc. Predominantly, the CSS scheme decreases the probabilities of miss-detection and false alarm considerably. The CSS is also mapped into multiple primary users (PU) detection schemes using orthogonal frequency division multiplexing (OFDM) technique. In this paper, we introduce a novel multi-band joint detection scheme known as wide-band spectrum sensing (WSS) in cognitive radio networks (CRN) that jointly detects various available channels rather than one frequency at a time. The proposed WSS not only enhances the dynamic spectrum utilization but also lowers the interference to the PUs. Furthermore, by lowering the PU’s interference over AWGN channel, the optimal solutions for WSS under non-cooperative and cooperative systems are investigated. This work formulates the mathematical framework for measuring miss-detection as well as total error probability (TEP). The derived analytical expressions are validated through MATLAB-based simulations. From the simulated results, it can be deduced that the proposed WSS scheme significantly enhances the performance of the system when compared with the conventional CSS schemes.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114998409","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9908609
Mahammad Aamir Mahmood, Obaidur Rahman, S. A. Khan
In this work, an effort is being made to calibrate a cross capacitive sensor when used to measure the concentration of insulation degradation parameters in transformer oil. The cross capacitive sensor offers many privileges in oil-based sensing. Moisture and 2-furfuraldehyde (2-FAL) are the two most important insulation degradation by- products. The concentration of moisture and 2-FAL with in the oil has been directly related to the condition of transformer insulation. The cross-capacitive sensor is calibrated using regression analysis for the measurement of 2-FAL, moisture and mixture of 2-FAL and moisture in the oil.
{"title":"Calibration of Cross Capacitive Sensor used for Transformer Oil Testing","authors":"Mahammad Aamir Mahmood, Obaidur Rahman, S. A. Khan","doi":"10.1109/ASIANCON55314.2022.9908609","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908609","url":null,"abstract":"In this work, an effort is being made to calibrate a cross capacitive sensor when used to measure the concentration of insulation degradation parameters in transformer oil. The cross capacitive sensor offers many privileges in oil-based sensing. Moisture and 2-furfuraldehyde (2-FAL) are the two most important insulation degradation by- products. The concentration of moisture and 2-FAL with in the oil has been directly related to the condition of transformer insulation. The cross-capacitive sensor is calibrated using regression analysis for the measurement of 2-FAL, moisture and mixture of 2-FAL and moisture in the oil.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125206657","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909362
Ravi Hosamani, Govindaraj Tonape, Harshavardhana Mannur, Basavaraj Neelagund
For wireless communication, low-power modulators are Widely used because of their efficiency. Quadrature Amplitude Modulation (QAM) is one of the popularly employed modulation Techniques for high data rate transmission. This paper describes the analysis of the parameters like power and area of 32bit and 64bit QAM modulators. In this proposed approach, a Lookup table is used to store cosine and sine wave data generated using traditional methods. To generate the output signal, the stored data is chosen on the input data stream. The modulator is simulated and synthesized, and results are compared in 180nm, 90nm, and 45nm in Cadence’s genus tool. The proposed model is designed and developed in Verilog code using cadence. The layout of the 64qam modulator is carried out in the cadence’s innovus tools with 45nm technology.
{"title":"Design of QAM in 45nm Using Cadence Tool","authors":"Ravi Hosamani, Govindaraj Tonape, Harshavardhana Mannur, Basavaraj Neelagund","doi":"10.1109/ASIANCON55314.2022.9909362","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909362","url":null,"abstract":"For wireless communication, low-power modulators are Widely used because of their efficiency. Quadrature Amplitude Modulation (QAM) is one of the popularly employed modulation Techniques for high data rate transmission. This paper describes the analysis of the parameters like power and area of 32bit and 64bit QAM modulators. In this proposed approach, a Lookup table is used to store cosine and sine wave data generated using traditional methods. To generate the output signal, the stored data is chosen on the input data stream. The modulator is simulated and synthesized, and results are compared in 180nm, 90nm, and 45nm in Cadence’s genus tool. The proposed model is designed and developed in Verilog code using cadence. The layout of the 64qam modulator is carried out in the cadence’s innovus tools with 45nm technology.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127176014","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909237
R. Kumari, M. Angira
This paper explores the impact of various switching structure geometries on the RF performance of a shunt capacitive switch. The switch geometries have been analysed as an electrical model in order to develop an understanding of the effect of geometrical changes in terms of scattering (S) parameters which affects the RF response of the switch. A RF-MEMS capacitive switch is built into a finite element method (FEM) based RF tool and the effect of meandering, actuation area, and further dielectric thickness have been analysed in this work. It is investigated that with an increase in the number of meanders, switch resistance and inductance have increased and thus the isolation peak is shifted towards low frequencies compared to the design having a low number of meanders. The switch with a smaller central overlap area has a good on-state response compared to the design having more central overlap area. Furthermore, reduction of dielectric thickness affects unactuated state response by tuning isolation to lower frequencies with a wider range of under 20 dB response points. As a result of the understandings gained from analysed structural modifications, designers can optimize the RF performance of the capacitive shunt switch in the desired frequency range.
{"title":"Investigation on Switching Structure Geometries and their Impact on Electromagnetic Response of RF-MEMS Capacitive Switch","authors":"R. Kumari, M. Angira","doi":"10.1109/ASIANCON55314.2022.9909237","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909237","url":null,"abstract":"This paper explores the impact of various switching structure geometries on the RF performance of a shunt capacitive switch. The switch geometries have been analysed as an electrical model in order to develop an understanding of the effect of geometrical changes in terms of scattering (S) parameters which affects the RF response of the switch. A RF-MEMS capacitive switch is built into a finite element method (FEM) based RF tool and the effect of meandering, actuation area, and further dielectric thickness have been analysed in this work. It is investigated that with an increase in the number of meanders, switch resistance and inductance have increased and thus the isolation peak is shifted towards low frequencies compared to the design having a low number of meanders. The switch with a smaller central overlap area has a good on-state response compared to the design having more central overlap area. Furthermore, reduction of dielectric thickness affects unactuated state response by tuning isolation to lower frequencies with a wider range of under 20 dB response points. As a result of the understandings gained from analysed structural modifications, designers can optimize the RF performance of the capacitive shunt switch in the desired frequency range.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"234 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127533614","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909355
Gopal Gupta, M. Sreejeth
With the increasing use of Electric Vehicle, Brushless DC Motor is gaining ground as its mainly used in 2W and 3W. For efficient controlling of Brushless DC Motor, Field Oriented Control becomes prominent. This paper presents the Field Oriented Control of Brushless DC Motor Drive using Hysteresis Control Technique. FOC algorithm is derived from the dynamic modelling of Brushless DC Motor. The simulation and modelling of BLDC Drive is done in MATLAB/Simulink Environment.
{"title":"Study and Analysis of Field Oriented Control of Brushless DC Motor Drive using Hysteresis Current Control Technique","authors":"Gopal Gupta, M. Sreejeth","doi":"10.1109/ASIANCON55314.2022.9909355","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909355","url":null,"abstract":"With the increasing use of Electric Vehicle, Brushless DC Motor is gaining ground as its mainly used in 2W and 3W. For efficient controlling of Brushless DC Motor, Field Oriented Control becomes prominent. This paper presents the Field Oriented Control of Brushless DC Motor Drive using Hysteresis Control Technique. FOC algorithm is derived from the dynamic modelling of Brushless DC Motor. The simulation and modelling of BLDC Drive is done in MATLAB/Simulink Environment.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125062924","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909156
Swati Patil, Snehal R. Rathi, Vaibhav Mankar
Chest diseases are one of the common diseases in humans, many viral borne diseases also attack the respiratory systems. In such situations, it becomes very important to detect and cure the disease as soon as possible. The chest x-ray is one of the most important sources to detect and identify chest disease. However, detecting the disease can be complicated and may require several medical tests. With the advancement in computer vision technologies, machines can extract information from images. We have trained the computer vision-based models for the task of phenomena disease delectation from the chest x-ray images. In this research paper, we present the novel approach for disease delectation using the ribs extractor framework. The ribs extractor model presented in this research paper was developed using the Conditional generative adversarial network. We have used CNN, densenet, resnet, VGG, and vision, transformer models. We have employed the transfer learning techniques for densenet, resnet, and VGG models. We also present the comparative study of the computer vision models without and with ribs extractor. Finally, we discuss the future scope and suggest ways to improve computer-aided disease detection. We hope that this research helps the research community to better understand medical image centric disease detection.
胸部疾病是人类常见疾病之一，许多病毒性疾病也会侵袭呼吸系统。在这种情况下，尽快发现和治愈疾病就变得非常重要。胸部 X 光是检测和识别胸部疾病的最重要来源之一。然而，疾病的检测可能比较复杂，需要进行多项医学检查。随着计算机视觉技术的发展，机器可以从图像中提取信息。我们训练了基于计算机视觉的模型，用于从胸部 X 光图像中发现疾病现象。在本研究论文中，我们介绍了使用肋骨提取器框架进行疾病选择的新方法。本研究论文中介绍的肋骨提取模型是利用条件生成对抗网络开发的。我们使用了 CNN、densenet、resnet、VGG 和视觉转换器模型。我们对 densenet、resnet 和 VGG 模型采用了迁移学习技术。我们还对不带肋骨提取器和带肋骨提取器的计算机视觉模型进行了比较研究。最后，我们讨论了未来的发展方向，并提出了改进计算机辅助疾病检测的方法。我们希望这项研究能帮助研究界更好地理解以医学影像为中心的疾病检测。
{"title":"A Novel Approach to Chest Disease Detection from Chest X-Ray Images","authors":"Swati Patil, Snehal R. Rathi, Vaibhav Mankar","doi":"10.1109/ASIANCON55314.2022.9909156","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909156","url":null,"abstract":"Chest diseases are one of the common diseases in humans, many viral borne diseases also attack the respiratory systems. In such situations, it becomes very important to detect and cure the disease as soon as possible. The chest x-ray is one of the most important sources to detect and identify chest disease. However, detecting the disease can be complicated and may require several medical tests. With the advancement in computer vision technologies, machines can extract information from images. We have trained the computer vision-based models for the task of phenomena disease delectation from the chest x-ray images. In this research paper, we present the novel approach for disease delectation using the ribs extractor framework. The ribs extractor model presented in this research paper was developed using the Conditional generative adversarial network. We have used CNN, densenet, resnet, VGG, and vision, transformer models. We have employed the transfer learning techniques for densenet, resnet, and VGG models. We also present the comparative study of the computer vision models without and with ribs extractor. Finally, we discuss the future scope and suggest ways to improve computer-aided disease detection. We hope that this research helps the research community to better understand medical image centric disease detection.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125851195","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}
In this paper, a 2D Photonic crystal based optical biosensor has been proposed and modelled for the detection of malaria. The model comprises of an optical micro ring resonator. The variation in the refractive index (RI) of the human blood cells has been observed from the normal to the infected one. This variation leads to the shift in intensity of the light and helps to detect whether the cell is normal or infected. The proposed design has high sensitivity of 942.8 nm/RIU with a Q-factor of around 750. The simulation and analysis of the design has been done using Finite difference time domain (FDTD) method.
{"title":"Modelling of 2D Photonic Crystal based Micro Ring Resonator Sensor for the Detection of Malaria","authors":"Rupinder Kaur, Gaurav Kumar Bharti, Ashutosh Tripathi","doi":"10.1109/ASIANCON55314.2022.9909063","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909063","url":null,"abstract":"In this paper, a 2D Photonic crystal based optical biosensor has been proposed and modelled for the detection of malaria. The model comprises of an optical micro ring resonator. The variation in the refractive index (RI) of the human blood cells has been observed from the normal to the infected one. This variation leads to the shift in intensity of the light and helps to detect whether the cell is normal or infected. The proposed design has high sensitivity of 942.8 nm/RIU with a Q-factor of around 750. The simulation and analysis of the design has been done using Finite difference time domain (FDTD) method.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126002540","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909402
Sayantan Shaw
Open source python libraries to implement linear operators are finding widespread applications in solving different problems of seismic data processing and interpretation. One such attempt has been made to invert acoustic impedance of layered earth structure from seismic reflection response observed on the earth’s surface. The present algorithm combines two established approaches, viz. i) using correlation as the adjoint operator of convolution and ii) using conjugate gradient solver as an alternative to matrix inversion-a commonly used method to solve constrained optimization problems. Time integration of the derived reflectivity from the inversion of observed seismic amplitude using the above two steps gives rise to bandpass acoustic impedance, thereby, enhancing the interpretive value of the results. The proposed algorithm has been tested on a two-dimensional wedge model and found to fare well for both noise free and noise corrupted synthetic data. Application on real field example from Teapot Dome 3D survey shows that the derived band pass acoustic impedance matches favorably with the acoustic impedance measured in a borehole.
{"title":"Open Source Python Libraries: An Application to Seismic Reservoir Characterization","authors":"Sayantan Shaw","doi":"10.1109/ASIANCON55314.2022.9909402","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909402","url":null,"abstract":"Open source python libraries to implement linear operators are finding widespread applications in solving different problems of seismic data processing and interpretation. One such attempt has been made to invert acoustic impedance of layered earth structure from seismic reflection response observed on the earth’s surface. The present algorithm combines two established approaches, viz. i) using correlation as the adjoint operator of convolution and ii) using conjugate gradient solver as an alternative to matrix inversion-a commonly used method to solve constrained optimization problems. Time integration of the derived reflectivity from the inversion of observed seismic amplitude using the above two steps gives rise to bandpass acoustic impedance, thereby, enhancing the interpretive value of the results. The proposed algorithm has been tested on a two-dimensional wedge model and found to fare well for both noise free and noise corrupted synthetic data. Application on real field example from Teapot Dome 3D survey shows that the derived band pass acoustic impedance matches favorably with the acoustic impedance measured in a borehole.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126185544","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9908942
Shital Kakad, Sudhir Dhage
Ontology construction takes a lot of effort and time. Semantic web extract accurate knowledge from large databases. In this paper, an ontology construction process is proposed for cross domain data. The amazon and flip kart reviews are taken to construct ontology for unstructured text data . The data is pre-processed to clean and remove noise. The combined approach of cosine similarity and TF-IDF has been used to find similarity. Further, K means clustering is applied to identify topics. The hierarchical clustering is implemented to represent ontology. The accuracy, precision and recall are calculated by applying different classifier algorithms like Decision Tree Classifier, Gaussian NB, Random Forest Classifier, Support vector classifier and, K Neighbors Classifier. Support vector classifiers show excellent results comparative to other classifier algorithms. Support vector classifier performance shows accuracy - 0.70%, precision- 0.83% , recall- 0.70% and F1-score - 0.73%.
{"title":"Ontology Construction and Knowledge Graph for Cross Domain Unstructured Text","authors":"Shital Kakad, Sudhir Dhage","doi":"10.1109/ASIANCON55314.2022.9908942","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908942","url":null,"abstract":"Ontology construction takes a lot of effort and time. Semantic web extract accurate knowledge from large databases. In this paper, an ontology construction process is proposed for cross domain data. The amazon and flip kart reviews are taken to construct ontology for unstructured text data . The data is pre-processed to clean and remove noise. The combined approach of cosine similarity and TF-IDF has been used to find similarity. Further, K means clustering is applied to identify topics. The hierarchical clustering is implemented to represent ontology. The accuracy, precision and recall are calculated by applying different classifier algorithms like Decision Tree Classifier, Gaussian NB, Random Forest Classifier, Support vector classifier and, K Neighbors Classifier. Support vector classifiers show excellent results comparative to other classifier algorithms. Support vector classifier performance shows accuracy - 0.70%, precision- 0.83% , recall- 0.70% and F1-score - 0.73%.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125274233","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 : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9908823
S. Bobde, Siddharth Shenoy, Omkar Shete, Omkar Shinde, Harsh Jhunjhunuwala
Over the years, many researchers have sought to use Deep Learning techniques to detect the malaria-infected cells in blood sample images. Although extremely dangerous, the spread of malaria can be restricted when treated in the early stages. This serves as an impetus for implementing an accurate solution for the detection of malaria that can replace the traditional manual process. The manual process consists of visually examining the blood samples and counting the parasitized and non-parasitized red blood cells. This process is extremely time-consuming, requires the presence of trained medical personnel, and is susceptible to human errors. With these aspects in mind, we aimed to develop a solution that could be used by medical staff with minimal training, thereby saving on time and labour. Having studied various research papers related to the use of Deep Learning techniques for the detection of malaria, we have proposed a model that addresses the gaps we identified in these systems while not compromising on the accuracy of the results. Our proposed model comprises a pre-processing module, the frozen Encoder of an Autoencoder model, a few dense CNN layers, and the classifier (Softmax).
{"title":"Malaria Cell Image Classification using Autoencoder","authors":"S. Bobde, Siddharth Shenoy, Omkar Shete, Omkar Shinde, Harsh Jhunjhunuwala","doi":"10.1109/ASIANCON55314.2022.9908823","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908823","url":null,"abstract":"Over the years, many researchers have sought to use Deep Learning techniques to detect the malaria-infected cells in blood sample images. Although extremely dangerous, the spread of malaria can be restricted when treated in the early stages. This serves as an impetus for implementing an accurate solution for the detection of malaria that can replace the traditional manual process. The manual process consists of visually examining the blood samples and counting the parasitized and non-parasitized red blood cells. This process is extremely time-consuming, requires the presence of trained medical personnel, and is susceptible to human errors. With these aspects in mind, we aimed to develop a solution that could be used by medical staff with minimal training, thereby saving on time and labour. Having studied various research papers related to the use of Deep Learning techniques for the detection of malaria, we have proposed a model that addresses the gaps we identified in these systems while not compromising on the accuracy of the results. Our proposed model comprises a pre-processing module, the frozen Encoder of an Autoencoder model, a few dense CNN layers, and the classifier (Softmax).","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114935529","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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