Pub Date : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974501
Weizun Wang, Jie Huang, A. Hu, Mengjia Ding, Jiabao Yu
Recently, remote keyless entry system (RKE system) has been gradually replacing traditional way to unlock car doors for convenience. However, it has been shown that RKE system is vulnerable to cyber attacks including relay attack, amplification attack and cryptographic attack. In order to solve this dilemma, RF fingerprints method was applied to identify car key fobs in this paper. Power spectrum of preamble signal envelope was proposed to extract features while carrier frequency offset and least mean square-based adaptive filter were also used as auxiliary ones. Multi-dimension RF fingerprints were presented in this paper based on three features mentioned above to increase identification accuracy. Support vector machine(SVM) was chosen with 10-fold cross-validation to train classifier model. Corresponding to current research on keyless entry car theft, the classification results in this paper show that signals from various key fobs can be classified with 99.3% accuracy when using Rf fingerprints extracted from multiple features, with false acceptance rate (FAR) of 0.7% and false rejection rate (FRR) of 0.7% under Multiple Discriminant Analysis, Maximum Likelihood (MDA/ML) classifier.
{"title":"Identification Technology of RKE System Using Multi-dimension RF Fingerprints","authors":"Weizun Wang, Jie Huang, A. Hu, Mengjia Ding, Jiabao Yu","doi":"10.1109/CCISP55629.2022.9974501","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974501","url":null,"abstract":"Recently, remote keyless entry system (RKE system) has been gradually replacing traditional way to unlock car doors for convenience. However, it has been shown that RKE system is vulnerable to cyber attacks including relay attack, amplification attack and cryptographic attack. In order to solve this dilemma, RF fingerprints method was applied to identify car key fobs in this paper. Power spectrum of preamble signal envelope was proposed to extract features while carrier frequency offset and least mean square-based adaptive filter were also used as auxiliary ones. Multi-dimension RF fingerprints were presented in this paper based on three features mentioned above to increase identification accuracy. Support vector machine(SVM) was chosen with 10-fold cross-validation to train classifier model. Corresponding to current research on keyless entry car theft, the classification results in this paper show that signals from various key fobs can be classified with 99.3% accuracy when using Rf fingerprints extracted from multiple features, with false acceptance rate (FAR) of 0.7% and false rejection rate (FRR) of 0.7% under Multiple Discriminant Analysis, Maximum Likelihood (MDA/ML) classifier.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123391187","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974289
Joel M. Gumiran, Arnel F. Fajardo, Ruji P. Medina
Phenotyping, mainly plant’ health monitoring, is labor-and time-intensive, particularly for large-scale operations like maize plantations. Therefore, this research used a drone equipped with an RGB image to photograph the whole plantation quickly. On the other hand, RGB photographs do not categorize plants and weeds due to high brightness, shadows, and overlapped foliage. Therefore, several segmentation algorithms are used to solve various challenges. For instance, threshold-based segmentation can only accept progressive illumination, which is crucial for outdoor lighting, simplicity, and distinguishing objects with identical hues. For this kind of segmentation, however, intense light requires modification. Consequently, threshold-based segmentation was improved to normalize the disturbances above while rapidly separating leaves from weeds. In this manner, the Enhanced threshold-based segmentation had applied to RGB images of maize plantations like cornfields with distractions seen in the gathered photos with a segmentation accuracy of 92.41%. In comparison, the threshold-based segmentation had used in the same dataset without normalizing the picture's luminance, with a segmentation accuracy of 5.71%. Thus, the enhanced segmentation method improved segmentation accuracy by 86.7% compared to threshold-based segmentation, which is limited to extreme light conditions. Thus, the incorporated normalization in the segmentation process significantly increases the segmentation accuracy.
{"title":"Enhanced Threshold-based Segmentation for Maize Plantation","authors":"Joel M. Gumiran, Arnel F. Fajardo, Ruji P. Medina","doi":"10.1109/CCISP55629.2022.9974289","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974289","url":null,"abstract":"Phenotyping, mainly plant’ health monitoring, is labor-and time-intensive, particularly for large-scale operations like maize plantations. Therefore, this research used a drone equipped with an RGB image to photograph the whole plantation quickly. On the other hand, RGB photographs do not categorize plants and weeds due to high brightness, shadows, and overlapped foliage. Therefore, several segmentation algorithms are used to solve various challenges. For instance, threshold-based segmentation can only accept progressive illumination, which is crucial for outdoor lighting, simplicity, and distinguishing objects with identical hues. For this kind of segmentation, however, intense light requires modification. Consequently, threshold-based segmentation was improved to normalize the disturbances above while rapidly separating leaves from weeds. In this manner, the Enhanced threshold-based segmentation had applied to RGB images of maize plantations like cornfields with distractions seen in the gathered photos with a segmentation accuracy of 92.41%. In comparison, the threshold-based segmentation had used in the same dataset without normalizing the picture's luminance, with a segmentation accuracy of 5.71%. Thus, the enhanced segmentation method improved segmentation accuracy by 86.7% compared to threshold-based segmentation, which is limited to extreme light conditions. Thus, the incorporated normalization in the segmentation process significantly increases the segmentation accuracy.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123471235","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974287
Yudong Wang, Zhou Yi
Reconfigurable optical splitter multiplexer (ROADM) devices are the core devices for current optical network interconnection and dense wavelength division multiplexing. In this paper, the Google Remote Procedure Call (gRPC) protocol is investigated for the shortcomings of low transmission rate, poor transmission efficiency and only local calls when communicating with RESTful and TCP protocols mainly used in the current ROADM device software calling system. A reconfigurable remote procedure call framework for optical splitter and multiplexer based on the gRPC protocol was implemented using C language. The shortcomings of the ROADM device call system in terms of transfer rate, transfer efficiency and the fact that only local procedure calls can be made have been improved. Test results show that the use of the gRPC protocol has effectively improved the transmission rate and efficiency of the RODAM device and enabled remote procedure calls.
{"title":"Reconfigurable optical demultiplexer calling framework based on gRPC Design","authors":"Yudong Wang, Zhou Yi","doi":"10.1109/CCISP55629.2022.9974287","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974287","url":null,"abstract":"Reconfigurable optical splitter multiplexer (ROADM) devices are the core devices for current optical network interconnection and dense wavelength division multiplexing. In this paper, the Google Remote Procedure Call (gRPC) protocol is investigated for the shortcomings of low transmission rate, poor transmission efficiency and only local calls when communicating with RESTful and TCP protocols mainly used in the current ROADM device software calling system. A reconfigurable remote procedure call framework for optical splitter and multiplexer based on the gRPC protocol was implemented using C language. The shortcomings of the ROADM device call system in terms of transfer rate, transfer efficiency and the fact that only local procedure calls can be made have been improved. Test results show that the use of the gRPC protocol has effectively improved the transmission rate and efficiency of the RODAM device and enabled remote procedure calls.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"532 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123935984","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974164
Yang Li, Sanxin Jiang
To realize the automatic detection of wafer surface defects, we propose Skip-MemGANs unsupervised detection network, which is an ensemble generative adversarial network that automatically detects defects by the difference between the target image and the reconstructed image.The network is composed of three generators and three discriminators. Each generator uses encoder-decoder convolutional neural network with two layers of skip connection and memory module to capture multi-scale input image features. These generators are randomly paired with discriminators, and receive feedback from the three discriminators, while the discriminators receive reconstructed samples from the three generators.Compared with a single GAN, the ensemble GAN can better simulate the distribution of normal data in the high-dimensional image space.We evaluate the single GAN model, GAN ensemble model and other basic models. The results show that our proposed Skip-MemGANs network outperforms other models in wafer defect detection task, the AUC value reached 0.956.
{"title":"Skip-MemGANs: An Ensemble Generative Adversarial Network Based on Skip Connection and Memory Module for Wafer Defect Detection","authors":"Yang Li, Sanxin Jiang","doi":"10.1109/CCISP55629.2022.9974164","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974164","url":null,"abstract":"To realize the automatic detection of wafer surface defects, we propose Skip-MemGANs unsupervised detection network, which is an ensemble generative adversarial network that automatically detects defects by the difference between the target image and the reconstructed image.The network is composed of three generators and three discriminators. Each generator uses encoder-decoder convolutional neural network with two layers of skip connection and memory module to capture multi-scale input image features. These generators are randomly paired with discriminators, and receive feedback from the three discriminators, while the discriminators receive reconstructed samples from the three generators.Compared with a single GAN, the ensemble GAN can better simulate the distribution of normal data in the high-dimensional image space.We evaluate the single GAN model, GAN ensemble model and other basic models. The results show that our proposed Skip-MemGANs network outperforms other models in wafer defect detection task, the AUC value reached 0.956.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115295919","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974378
C. Ding
Living age inference plays an important role in the study of court science related cases, especially in adolescence and early adulthood. It is more and more important to infer the age of the living body by using the imaging characteristics of human teeth and bones in judicial practice. Through the analysis and summary of the latest application of image examination technology in the estimation of living age, the analysis methods and common indicators involved in different examination methods are summarized, and the advantages, disadvantages and development trends of relevant examinations are summarized, so as to provide research ideas for the estimation of living age.
{"title":"Recent advances in the application of imaging techniques in the estimation of living age","authors":"C. Ding","doi":"10.1109/CCISP55629.2022.9974378","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974378","url":null,"abstract":"Living age inference plays an important role in the study of court science related cases, especially in adolescence and early adulthood. It is more and more important to infer the age of the living body by using the imaging characteristics of human teeth and bones in judicial practice. Through the analysis and summary of the latest application of image examination technology in the estimation of living age, the analysis methods and common indicators involved in different examination methods are summarized, and the advantages, disadvantages and development trends of relevant examinations are summarized, so as to provide research ideas for the estimation of living age.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116671164","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974268
Chunyang Li, Guang-xin Wu, Gui Li
The integrated detection and jamming signal, which can realize radar detection and jamming functions at the same time, is becoming more and more important today when multifunctional integrated RF systems are of great interest. In this paper, we propose an integrated signal with Costas coding of the intra-pulse frequency of LFM signal. The integrated signal has an ideal ambiguity function of pin type and is capable of causing varying degrees of coherent jamming to the enemy's LFM signal. According to the principle of time-domain matched filtering, we deduce the false target group form of this signal at enemy. Then the jamming performance of this signal is deduced and analyzed according to the difference of Costas sequences. Finally, the theoretical derivation and analysis of the jamming effect of this signal are verified by the simulation results.
{"title":"A Shared Waveform Design for Integrated Detection and Jamming Signal Based on LFM-Costas Intra-pulse Frequency Stepping","authors":"Chunyang Li, Guang-xin Wu, Gui Li","doi":"10.1109/CCISP55629.2022.9974268","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974268","url":null,"abstract":"The integrated detection and jamming signal, which can realize radar detection and jamming functions at the same time, is becoming more and more important today when multifunctional integrated RF systems are of great interest. In this paper, we propose an integrated signal with Costas coding of the intra-pulse frequency of LFM signal. The integrated signal has an ideal ambiguity function of pin type and is capable of causing varying degrees of coherent jamming to the enemy's LFM signal. According to the principle of time-domain matched filtering, we deduce the false target group form of this signal at enemy. Then the jamming performance of this signal is deduced and analyzed according to the difference of Costas sequences. Finally, the theoretical derivation and analysis of the jamming effect of this signal are verified by the simulation results.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121831214","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}
Inverse synthetic aperture radar (ISAR) image offers geometric and structural characteristics information of target objects. Thus, It is an important research topic to recognize radar targets based on ISAR images. ISAR imaging offers the advantages of all-day, all-weather, and ultra-long- distance imaging; however, ISAR image quality is affected by attitude angle, defocusing noise, resolution and other factors, resulting in inferior recognition performance. In contrast, optical images require more stringent imaging conditions, but they provide more feature diversity, resulting in a better recognition effect. Combining the advantages of ISAR images and optical images, the transformation from target ISAR images to optical images greatly improves the target recognition performance. In this study, an ISAR-to-optical image generation method was developed. Combined with two attention mechanisms and the SSIM loss function, a conditional generative adversarial network was constructed to transform ISAR images into optical images so that the generative model can realistically restore the details of the target images. In addition, a comparative test was conducted on a simulated aircraft target, and the performance of the proposed architecture was evaluated in terms of visual effects and quantitative indicators. The results show that the proposed method yields better generation effect. Furthermore, the target recognition case shows that the recognition rate obtained using the generated optical images is considerably higher than that obtained using the original ISAR images, further verifying the effectiveness of the generated image for target recognition.
{"title":"A-CGAN based transformation from ISAR to optical image","authors":"Qinwen Tan, Xiangyuan Li, Zhen Liu, Shuowei Liu, Qinmu Shen","doi":"10.1109/CCISP55629.2022.9974485","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974485","url":null,"abstract":"Inverse synthetic aperture radar (ISAR) image offers geometric and structural characteristics information of target objects. Thus, It is an important research topic to recognize radar targets based on ISAR images. ISAR imaging offers the advantages of all-day, all-weather, and ultra-long- distance imaging; however, ISAR image quality is affected by attitude angle, defocusing noise, resolution and other factors, resulting in inferior recognition performance. In contrast, optical images require more stringent imaging conditions, but they provide more feature diversity, resulting in a better recognition effect. Combining the advantages of ISAR images and optical images, the transformation from target ISAR images to optical images greatly improves the target recognition performance. In this study, an ISAR-to-optical image generation method was developed. Combined with two attention mechanisms and the SSIM loss function, a conditional generative adversarial network was constructed to transform ISAR images into optical images so that the generative model can realistically restore the details of the target images. In addition, a comparative test was conducted on a simulated aircraft target, and the performance of the proposed architecture was evaluated in terms of visual effects and quantitative indicators. The results show that the proposed method yields better generation effect. Furthermore, the target recognition case shows that the recognition rate obtained using the generated optical images is considerably higher than that obtained using the original ISAR images, further verifying the effectiveness of the generated image for target recognition.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"214 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121202685","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974216
Ming Xu, Yuhang Wu, Hao Zhang, Lu Yuan, Yiyao Wan, Fuhui Zhou, Qihui Wu
Unmanned aerial vehicle (UAV) recognition is of crucial importance due to the blowout amount of UAVs and their threats on the public safety. Although many UAV recognition methods based on deep learning (DL) have been proposed by utilizing the radio frequency fingerprints and have achieved appreciable results, their vulnerability to adversarial attacks, especially backdoor attacks, has not been studied. In this pa-per, in order to reveal the serious threat for DL-based UAV recognition encountered with backdoor attacks, a novel robust generative adversarial network (GAN)-enabled backdoor attack scheme is proposed. Moreover, the proposed GAN-based trigger generator not only emerges exceptional attack effectiveness, but also performs well in terms of attack stealthiness and migration ability. Simulation results obtained with the real collected UAV recognition dataset demonstrate that our proposed scheme outperforms the benchmark BadNets backdoor attack.
{"title":"GAN-Enabled Robust Backdoor Attack for UAV Recognition","authors":"Ming Xu, Yuhang Wu, Hao Zhang, Lu Yuan, Yiyao Wan, Fuhui Zhou, Qihui Wu","doi":"10.1109/CCISP55629.2022.9974216","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974216","url":null,"abstract":"Unmanned aerial vehicle (UAV) recognition is of crucial importance due to the blowout amount of UAVs and their threats on the public safety. Although many UAV recognition methods based on deep learning (DL) have been proposed by utilizing the radio frequency fingerprints and have achieved appreciable results, their vulnerability to adversarial attacks, especially backdoor attacks, has not been studied. In this pa-per, in order to reveal the serious threat for DL-based UAV recognition encountered with backdoor attacks, a novel robust generative adversarial network (GAN)-enabled backdoor attack scheme is proposed. Moreover, the proposed GAN-based trigger generator not only emerges exceptional attack effectiveness, but also performs well in terms of attack stealthiness and migration ability. Simulation results obtained with the real collected UAV recognition dataset demonstrate that our proposed scheme outperforms the benchmark BadNets backdoor attack.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125102764","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974290
Lingru Pei, Cheng-zhu Du, Chengxin Shi, HuanChen Peng
A dual-band MIMO antenna is proposed on the basis of artificial magnetic conductors (AMC). The MIMO antenna consists of two water lily shaped printed monopole antennas and an SRR isolation structure, operating at the ISM bands of 2.45GHz and 5.8GHz.A simple, compact double circle-based artificial magnetic conductor (AMC) reflector is introduced to decrease radiation exposure to people as well as increase forward gain. The antenna and the 4x4 AMC array are both printed on flexible substrate Rogers RO3003, thus the antenna system can follow the contours of the human body. According to the simulated results, the proposed antenna exhibits peak gains of 8.03 dBi and 8.43 dBi at 2.45GHz and 5.8GHz respectively. The SAR value of body tissue can be reduced by around 97% while the front-to-back ratio (FBR) is over 24.5dB. Its improved radiation characteristics compared to conventional monopole antennas make it a good candidate for WBAN and ISM applications.
{"title":"A gain enhanced low SAR dual-band MIMO antenna integrated with AMC for wearable ISM applications","authors":"Lingru Pei, Cheng-zhu Du, Chengxin Shi, HuanChen Peng","doi":"10.1109/CCISP55629.2022.9974290","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974290","url":null,"abstract":"A dual-band MIMO antenna is proposed on the basis of artificial magnetic conductors (AMC). The MIMO antenna consists of two water lily shaped printed monopole antennas and an SRR isolation structure, operating at the ISM bands of 2.45GHz and 5.8GHz.A simple, compact double circle-based artificial magnetic conductor (AMC) reflector is introduced to decrease radiation exposure to people as well as increase forward gain. The antenna and the 4x4 AMC array are both printed on flexible substrate Rogers RO3003, thus the antenna system can follow the contours of the human body. According to the simulated results, the proposed antenna exhibits peak gains of 8.03 dBi and 8.43 dBi at 2.45GHz and 5.8GHz respectively. The SAR value of body tissue can be reduced by around 97% while the front-to-back ratio (FBR) is over 24.5dB. Its improved radiation characteristics compared to conventional monopole antennas make it a good candidate for WBAN and ISM applications.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130314925","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 : 2022-11-01DOI: 10.1109/CCISP55629.2022.9974445
Jishen Peng, Jianbing Han, Yiling Yang
Aiming at the problems of manual processing and grinding workpieces, such as time-consuming and low accuracy, an intelligent method for grinding workpieces was proposed. The dataset is preprocessed using image graying and guided filtering. The mechanical arm is used for machining and grinding, Adding semantic segmentation technology to realize accurate identification and location of machining trajectory, An improved CascadePSP Net is proposed to realize faster recognition while ensuring accuracy. By comparing the improved CascadePSP Net with the original network, the segmentation accuracy and training speed are improved. Use the Sober operator to extract the contour of the workpiece to be machined to determine the final machining path. The trajectory planning of the three-degree-of-freedom Dobot Magician manipulator is carried out by the fifth-order polynomial interpolation method and the Cartesian coordinate system method. Build an experimental platform for an image recognition robotic arm, and the comparison of the trajectory recognition method and the test experiment of the mechanical arm grinding system were carried out respectively. It verifies the feasibility of the proposed grinding method. The experimental results show that the method reduces the network training time, realizes high-efficiency and high-precision segmentation processing, thus improves the workpiece grinding efficiency and realizes the intelligent processing of workpiece batches.
{"title":"Research on Mechanical Arm Grinding Method Based on Improved CascadePSP Net","authors":"Jishen Peng, Jianbing Han, Yiling Yang","doi":"10.1109/CCISP55629.2022.9974445","DOIUrl":"https://doi.org/10.1109/CCISP55629.2022.9974445","url":null,"abstract":"Aiming at the problems of manual processing and grinding workpieces, such as time-consuming and low accuracy, an intelligent method for grinding workpieces was proposed. The dataset is preprocessed using image graying and guided filtering. The mechanical arm is used for machining and grinding, Adding semantic segmentation technology to realize accurate identification and location of machining trajectory, An improved CascadePSP Net is proposed to realize faster recognition while ensuring accuracy. By comparing the improved CascadePSP Net with the original network, the segmentation accuracy and training speed are improved. Use the Sober operator to extract the contour of the workpiece to be machined to determine the final machining path. The trajectory planning of the three-degree-of-freedom Dobot Magician manipulator is carried out by the fifth-order polynomial interpolation method and the Cartesian coordinate system method. Build an experimental platform for an image recognition robotic arm, and the comparison of the trajectory recognition method and the test experiment of the mechanical arm grinding system were carried out respectively. It verifies the feasibility of the proposed grinding method. The experimental results show that the method reduces the network training time, realizes high-efficiency and high-precision segmentation processing, thus improves the workpiece grinding efficiency and realizes the intelligent processing of workpiece batches.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133309612","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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