Pub Date : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990560
Dung Manh Do, D. Hoang, NamHoai Nguyen, P. D. Nguyen
This article proposes a data-driven method for tracking control of the autonomous underwater vehicle (AUV) with matched disturbances and time-varying model’s uncertain parameters. The method is established by combining the conventional model reference control principle with a corresponding procedure for step-wise updating controller parameters so that the model error between the AUV and an appropriately chosen linear stable model converges to zero. The update procedure of controller parameters is created based on Lagrange interpolation technique, hence it acts entirely on the experimentally collected data from the AUV. The expected tracking performance by using this proposed data-driven controller has been theoretically authenticated and through numerical simulation.
{"title":"Data-Driven Output Regulation of Uncertain 6 DOF AUV via Lagrange Interpolation","authors":"Dung Manh Do, D. Hoang, NamHoai Nguyen, P. D. Nguyen","doi":"10.1109/ICCAIS56082.2022.9990560","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990560","url":null,"abstract":"This article proposes a data-driven method for tracking control of the autonomous underwater vehicle (AUV) with matched disturbances and time-varying model’s uncertain parameters. The method is established by combining the conventional model reference control principle with a corresponding procedure for step-wise updating controller parameters so that the model error between the AUV and an appropriately chosen linear stable model converges to zero. The update procedure of controller parameters is created based on Lagrange interpolation technique, hence it acts entirely on the experimentally collected data from the AUV. The expected tracking performance by using this proposed data-driven controller has been theoretically authenticated and through numerical simulation.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116988579","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990164
Nga Bui Thi Thuy, D. N. Bui, Manh Duong Phung, Hung Pham Duy
This study proposes an approach for establishing an optimal multihop ad-hoc network using multiple unmanned aerial vehicles (UAVs) to provide emergency communication in disaster areas. The approach includes two stages, one uses particle swarm optimization (PSO) to find optimal positions to deploy UAVs, and the other uses a behavior-based controller to navigate the UAVs to their assigned positions without colliding with obstacles in an unknown environment. Several constraints related to the UAVs’ sensing and communication ranges have been imposed to ensure the applicability of the proposed approach in real-world scenarios. A number of simulation experiments with data loaded from real environments have been conducted. The results show that our proposed approach is not only successful in establishing multihop ad-hoc routes but also meets the requirements for real-time deployment of UAVs.
{"title":"Deployment of UAVs for Optimal Multihop Ad-hoc Networks Using Particle Swarm Optimization and Behavior-based Control","authors":"Nga Bui Thi Thuy, D. N. Bui, Manh Duong Phung, Hung Pham Duy","doi":"10.1109/ICCAIS56082.2022.9990164","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990164","url":null,"abstract":"This study proposes an approach for establishing an optimal multihop ad-hoc network using multiple unmanned aerial vehicles (UAVs) to provide emergency communication in disaster areas. The approach includes two stages, one uses particle swarm optimization (PSO) to find optimal positions to deploy UAVs, and the other uses a behavior-based controller to navigate the UAVs to their assigned positions without colliding with obstacles in an unknown environment. Several constraints related to the UAVs’ sensing and communication ranges have been imposed to ensure the applicability of the proposed approach in real-world scenarios. A number of simulation experiments with data loaded from real environments have been conducted. The results show that our proposed approach is not only successful in establishing multihop ad-hoc routes but also meets the requirements for real-time deployment of UAVs.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114816346","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}
Nuclei segmentation, despite its fundamental role in histopathological image analysis, is still a challenge work. The main challenge of this task is the existence of overlapping areas, which makes separating independent nuclei more complicated. In this paper, we propose a new two-branch architecture by combining the Unet and TransUnet networks for nuclei segmentation task. In the proposed architecture, namely Trans2Unet, the input image is first sent into the Unet branch whose the last convolution layer is removed. This branch makes the network combine features from different spatial regions of the input image and localizes more precisely the regions of interest. The input image is also fed into the second branch. In the second branch, which is called TransUnet branch, the input image will be divided into patches of images. With Vision transformer (ViT) in architecture, TransUnet can serve as a powerful encoder for medical image segmentation tasks and enhance image details by recovering localized spatial information. To boost up Trans2Unet efficiency and performance, we proposed to infuse TransUnet with a computational-efficient variation called “Waterfall” Atrous Spatial Pooling with Skip Connection (WASP-KC) module, which is inspired by the “Waterfall” Atrous Spatial Pooling (WASP) module. Experiment results on the 2018 Data Science Bowl benchmark show the effectiveness and performance of the proposed architecture while compared with previous segmentation models.
{"title":"Trans2Unet: Neural fusion for Nuclei Semantic Segmentation","authors":"Dinh-Phu Tran, Quoc-Anh Nguyen, Van-Truong Pham, Thi-Thao Tran","doi":"10.1109/ICCAIS56082.2022.9990159","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990159","url":null,"abstract":"Nuclei segmentation, despite its fundamental role in histopathological image analysis, is still a challenge work. The main challenge of this task is the existence of overlapping areas, which makes separating independent nuclei more complicated. In this paper, we propose a new two-branch architecture by combining the Unet and TransUnet networks for nuclei segmentation task. In the proposed architecture, namely Trans2Unet, the input image is first sent into the Unet branch whose the last convolution layer is removed. This branch makes the network combine features from different spatial regions of the input image and localizes more precisely the regions of interest. The input image is also fed into the second branch. In the second branch, which is called TransUnet branch, the input image will be divided into patches of images. With Vision transformer (ViT) in architecture, TransUnet can serve as a powerful encoder for medical image segmentation tasks and enhance image details by recovering localized spatial information. To boost up Trans2Unet efficiency and performance, we proposed to infuse TransUnet with a computational-efficient variation called “Waterfall” Atrous Spatial Pooling with Skip Connection (WASP-KC) module, which is inspired by the “Waterfall” Atrous Spatial Pooling (WASP) module. Experiment results on the 2018 Data Science Bowl benchmark show the effectiveness and performance of the proposed architecture while compared with previous segmentation models.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126802535","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990266
T. V. Do, Pascal Messier, J. Trovão, L. Boulon
For each fuel cell (FC) system design, a constant operating temperature is frequently chosen to maximize its efficiency. Nevertheless, the temperature variation leads to changing the FC output at a given power. This adjustment in the FC current and voltage impacts the power electronics performance, thus influencing the performance of the fuel cell hybrid electric vehicle (FC-HEV). Therefore, this paper investigates the performance of coupling the FC and power electronics to choose this operating temperature. Firstly, an operating temperature adjustment model of the Proton Exchange Membrane Fuel Cell (PEMFC) system is established. The efficiency of the powertrain based on an embedded highperformance active switched quasi-Z-Source inverter (HP-ASqZSI) at various FC operating voltages is secondly realized by theoretical analysis. Opal-RT-based real-time simulation is then performed to validate the performance of the FC-HEV system against various temperatures in terms of efficiency and hydrogen consumption. Simulation results indicate that increasing the FC operating temperature from 25°C to 60°C and 70°C results in an improved FC-HEV efficiency by 1.09% and 1.14%, respectively. Moreover, the average total hydrogen consumption of the FC system is also decreased by 21.23% and 29.34%, respectively over the lowest operating temperature under the studied Artemis driving cycle.
{"title":"Operating Temperature Systemic Management of a Fuel Cell System Considering the Impact on the Power Electronics Performances","authors":"T. V. Do, Pascal Messier, J. Trovão, L. Boulon","doi":"10.1109/ICCAIS56082.2022.9990266","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990266","url":null,"abstract":"For each fuel cell (FC) system design, a constant operating temperature is frequently chosen to maximize its efficiency. Nevertheless, the temperature variation leads to changing the FC output at a given power. This adjustment in the FC current and voltage impacts the power electronics performance, thus influencing the performance of the fuel cell hybrid electric vehicle (FC-HEV). Therefore, this paper investigates the performance of coupling the FC and power electronics to choose this operating temperature. Firstly, an operating temperature adjustment model of the Proton Exchange Membrane Fuel Cell (PEMFC) system is established. The efficiency of the powertrain based on an embedded highperformance active switched quasi-Z-Source inverter (HP-ASqZSI) at various FC operating voltages is secondly realized by theoretical analysis. Opal-RT-based real-time simulation is then performed to validate the performance of the FC-HEV system against various temperatures in terms of efficiency and hydrogen consumption. Simulation results indicate that increasing the FC operating temperature from 25°C to 60°C and 70°C results in an improved FC-HEV efficiency by 1.09% and 1.14%, respectively. Moreover, the average total hydrogen consumption of the FC system is also decreased by 21.23% and 29.34%, respectively over the lowest operating temperature under the studied Artemis driving cycle.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133000362","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990413
N. Ikoma
Car driver’s hands motion operating the steering-wheel in a car cabin has been tracked based on multi-Bernoulli filter framework with the aid of semantic segmentation for body region extraction and hand landmarks detection over camera image, according to the newly proposed method in this paper. Real-time implementation of the method has been proposed as a hybrid system of python and C/C++ languages with CUDA GPU computation for particle filtering, DeepLab v3 for semantic segmentation, and MediaPipe for hand landmarks detector. Experimental results demonstrate improved performance of hands tracking especially by newly incorporated part of the hand landmarks detector.
{"title":"Hands Tracking over Steering Wheel based on Multi-Bernoulli Filter Framework with Hand Landmarks Detector and Semantic Segmentation","authors":"N. Ikoma","doi":"10.1109/ICCAIS56082.2022.9990413","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990413","url":null,"abstract":"Car driver’s hands motion operating the steering-wheel in a car cabin has been tracked based on multi-Bernoulli filter framework with the aid of semantic segmentation for body region extraction and hand landmarks detection over camera image, according to the newly proposed method in this paper. Real-time implementation of the method has been proposed as a hybrid system of python and C/C++ languages with CUDA GPU computation for particle filtering, DeepLab v3 for semantic segmentation, and MediaPipe for hand landmarks detector. Experimental results demonstrate improved performance of hands tracking especially by newly incorporated part of the hand landmarks detector.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133567007","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990398
N. D. Thuan, Hoang Si Hong
In this work, we propose a design of wireless smart shoes for running gait analysis. The system is based on an inertial measurement unit (IMU) and Bluetooth low energy (BLE) protocol to save energy. The estimated parameters include activity type (run/walk/rest), forward distance, and average moving speed. These parameters are calculated and displayed on the user’s smartphone. Different from previous works, IMU data is collected to train a compact neural network model for running gait classification. The performance of model prediction and other measurements is evaluated with a customized database of 600 data segments. Experimental results show that our model achieves a high accuracy of 99.35% on gait classification. Other measures for moving analysis such as the total forward distance and the average speed are retrieved with a low maximum error of less than 4.67% and 4.80% respectively.
{"title":"Wireless Smart Shoes for Running Gait Analysis Based on Deep Learning","authors":"N. D. Thuan, Hoang Si Hong","doi":"10.1109/ICCAIS56082.2022.9990398","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990398","url":null,"abstract":"In this work, we propose a design of wireless smart shoes for running gait analysis. The system is based on an inertial measurement unit (IMU) and Bluetooth low energy (BLE) protocol to save energy. The estimated parameters include activity type (run/walk/rest), forward distance, and average moving speed. These parameters are calculated and displayed on the user’s smartphone. Different from previous works, IMU data is collected to train a compact neural network model for running gait classification. The performance of model prediction and other measurements is evaluated with a customized database of 600 data segments. Experimental results show that our model achieves a high accuracy of 99.35% on gait classification. Other measures for moving analysis such as the total forward distance and the average speed are retrieved with a low maximum error of less than 4.67% and 4.80% respectively.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114677257","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990117
Lin Gao, G. Battistelli, L. Chisci
Recently, it has been proposed to deal with fusion of multi-object densities exploiting the minimum information loss (MIL) rule, which has shown its superiority over generalized covariance intersection (GCI) fusion whenever sensor nodes have low detection probability. On the contrary, GCI shows better performance than MIL when dense clutter is involved in the measurements. In this paper, we are going to study the behavior of multi-object fusion with MIL and, respectively, GCI rules in the situation wherein the sensor network is exposed to cyber-attacks. Both theoretical and numerical analyses demonstrate that MIL is more robust than GCI fusion when the multi-sensor system is subject to a packet substitution attack.
{"title":"Resilience of multi-object density fusion against cyber-attacks","authors":"Lin Gao, G. Battistelli, L. Chisci","doi":"10.1109/ICCAIS56082.2022.9990117","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990117","url":null,"abstract":"Recently, it has been proposed to deal with fusion of multi-object densities exploiting the minimum information loss (MIL) rule, which has shown its superiority over generalized covariance intersection (GCI) fusion whenever sensor nodes have low detection probability. On the contrary, GCI shows better performance than MIL when dense clutter is involved in the measurements. In this paper, we are going to study the behavior of multi-object fusion with MIL and, respectively, GCI rules in the situation wherein the sensor network is exposed to cyber-attacks. Both theoretical and numerical analyses demonstrate that MIL is more robust than GCI fusion when the multi-sensor system is subject to a packet substitution attack.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122502389","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990214
D. M. Huynh, A. Nguyen, H. Nguyen, H. Tran, Dung Daniel Ngo, J. Pestana, A. Q. Nguyen
In the development process of Unmanned Aerial Vehicles (UAVs), researchers have to solve a lot of complex problems such as unreliable pose estimation, sensor errors, unknown and fast-changing environments, which require a lot of test trials. However, real-world testing of UAVs is expensive, time-consuming, and requires a pilot and careful testing of the correct integration of the hardware and software components. As a result, the usage of simulation tools presents itself as a promising alternative to real flight tests. Therefore, having a nearly photo-realistic, Hardware in the Loop (HITL) enabled and accurate simulation tool integrated with a popular autopilot board would be advantageous to the research community. We propose an implementation of a high autonomy drone navigation architecture integrated with the photo-realistic environment simulator Flightmare Renderer, the flight-dynamics simulator Gazebo and a popular autopilot board Pixhawk (PX4) controller to make a photo-realistic and accurate dynamic simulation for drones. By means of our simulation, we evaluate the drone system architecture by running a full set of algorithms required to achieve full autonomy, which includes visual-inertial pose estimation, mapping, path planning, obstacle avoidance, and control modules. That means each individual module and the whole system are tested and evaluated on the photo-realistic rendering and accurate flight-dynamics simulation environment. Thanks to the integration of the PX4 autopilot with HITL simulation, the progress from simulation flight to real flight experiments is easier and faster.
{"title":"Implementation of a HITL-Enabled High Autonomy Drone Architecture on a Photo-Realistic Simulator","authors":"D. M. Huynh, A. Nguyen, H. Nguyen, H. Tran, Dung Daniel Ngo, J. Pestana, A. Q. Nguyen","doi":"10.1109/ICCAIS56082.2022.9990214","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990214","url":null,"abstract":"In the development process of Unmanned Aerial Vehicles (UAVs), researchers have to solve a lot of complex problems such as unreliable pose estimation, sensor errors, unknown and fast-changing environments, which require a lot of test trials. However, real-world testing of UAVs is expensive, time-consuming, and requires a pilot and careful testing of the correct integration of the hardware and software components. As a result, the usage of simulation tools presents itself as a promising alternative to real flight tests. Therefore, having a nearly photo-realistic, Hardware in the Loop (HITL) enabled and accurate simulation tool integrated with a popular autopilot board would be advantageous to the research community. We propose an implementation of a high autonomy drone navigation architecture integrated with the photo-realistic environment simulator Flightmare Renderer, the flight-dynamics simulator Gazebo and a popular autopilot board Pixhawk (PX4) controller to make a photo-realistic and accurate dynamic simulation for drones. By means of our simulation, we evaluate the drone system architecture by running a full set of algorithms required to achieve full autonomy, which includes visual-inertial pose estimation, mapping, path planning, obstacle avoidance, and control modules. That means each individual module and the whole system are tested and evaluated on the photo-realistic rendering and accurate flight-dynamics simulation environment. Thanks to the integration of the PX4 autopilot with HITL simulation, the progress from simulation flight to real flight experiments is easier and faster.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117158117","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990402
Ngoc-Du Tran, H. Lê, Van-Truong Pham, Thi-Thao Tran
Biometric technology is increasingly popular and has many practical applications in our lives, such as fingerprint recognition, face recognition, iris recognition, etc. In biometrics based recognition technologies, finger knuckle print recognition (FKP) has received a lot of research attention recently. This method has many advantages compared to the others such as fingerprint recognition and iris recognition. Motivated by the advantages of FKR and advances of deep learning, this paper proposes a finger knuckle print recognition model, namely KPmixer. In particular, we modify the Convmixer model using variable-size kernels to reduce the number of parameters of the model and help the model mix spatial information at various distances. At the same time, we recommend the SE+ module to increase the accuracy of FKP recognition. Moreover, we propose to use a set of effective data augmentation methods for FKP recognition. The performance of the proposed model is compared with modern CNN models such as Convmixer, Resnet18, MobileNet, and DenseNet, showing an outstanding result in terms of accuracy.
{"title":"KPmixer-a ConvMixer-based Network for Finger Knuckle Print Recognition","authors":"Ngoc-Du Tran, H. Lê, Van-Truong Pham, Thi-Thao Tran","doi":"10.1109/ICCAIS56082.2022.9990402","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990402","url":null,"abstract":"Biometric technology is increasingly popular and has many practical applications in our lives, such as fingerprint recognition, face recognition, iris recognition, etc. In biometrics based recognition technologies, finger knuckle print recognition (FKP) has received a lot of research attention recently. This method has many advantages compared to the others such as fingerprint recognition and iris recognition. Motivated by the advantages of FKR and advances of deep learning, this paper proposes a finger knuckle print recognition model, namely KPmixer. In particular, we modify the Convmixer model using variable-size kernels to reduce the number of parameters of the model and help the model mix spatial information at various distances. At the same time, we recommend the SE+ module to increase the accuracy of FKP recognition. Moreover, we propose to use a set of effective data augmentation methods for FKP recognition. The performance of the proposed model is compared with modern CNN models such as Convmixer, Resnet18, MobileNet, and DenseNet, showing an outstanding result in terms of accuracy.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123585228","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 : 2022-11-21DOI: 10.1109/ICCAIS56082.2022.9990345
Ke Chen, Lei Chai, Wei Yi
In this paper, a multi-sensor control method with limited sensor field-of-view (FoV) based on Poisson multi-Bernoulli mixture (PMBM) filter is proposed, which provides a solution to the multi-target joint search and tracking problem. First, we propose a robust fusion method for multi-sensor PMBM posterior densities with limited sensor FoV based on the generalized covariance intersection (GCI) fusion criterion. Then, a cost function is constructed for multi-sensor control based on the fused density, which takes into account both discovered and undiscovered targets. The optimal multi-sensor control scheme is obtained by minimizing the cost function. The effectiveness of the proposed control method is demonstrated through a multi-target joint search and tracking simulation with unknown and time-varying number of targets and limited FoVs of sensors.
{"title":"Multi-Sensor Control for Jointly Searching and Tracking Multi-Target Using the Poisson Multi-Bernoulli Mixture Filter","authors":"Ke Chen, Lei Chai, Wei Yi","doi":"10.1109/ICCAIS56082.2022.9990345","DOIUrl":"https://doi.org/10.1109/ICCAIS56082.2022.9990345","url":null,"abstract":"In this paper, a multi-sensor control method with limited sensor field-of-view (FoV) based on Poisson multi-Bernoulli mixture (PMBM) filter is proposed, which provides a solution to the multi-target joint search and tracking problem. First, we propose a robust fusion method for multi-sensor PMBM posterior densities with limited sensor FoV based on the generalized covariance intersection (GCI) fusion criterion. Then, a cost function is constructed for multi-sensor control based on the fused density, which takes into account both discovered and undiscovered targets. The optimal multi-sensor control scheme is obtained by minimizing the cost function. The effectiveness of the proposed control method is demonstrated through a multi-target joint search and tracking simulation with unknown and time-varying number of targets and limited FoVs of sensors.","PeriodicalId":273404,"journal":{"name":"2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124371076","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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