2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)最新文献

Broad Learning System with Particle Swarm Optimization and Singular Value Decomposition 基于粒子群优化和奇异值分解的广义学习系统

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642158

Huaying Sun, Shujun Wu, Guang-Fu Xue, Kai Zhang, Jian Wang

{"title":"Broad Learning System with Particle Swarm Optimization and Singular Value Decomposition","authors":"Huaying Sun, Shujun Wu, Guang-Fu Xue, Kai Zhang, Jian Wang","doi":"10.1109/ICICIP53388.2021.9642158","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642158","url":null,"abstract":"Broad Learning System (BLS), a newly-developing alternative approach of learning for deep neural network, has attracted much attentions from researchers all over the world due to its straightforward network structure and powerful performance to deal with classification and regression problems. The number of feature nodes and enhancement nodes in classical BLS is determined by grid search method which leads to heavy training burden, while the weights between input data and feature nodes are randomly initialized and fine-tuned taking advantages of sparse autoencoder. Different from that, a new BLS with Particle Swarm optimization (PSO) and Singular Value Decomposition (SVD) is raised in this paper. PSO algorithm is introduced to acquire the optimal number of feature nodes and enhancement nodes, which greatly reduces the search time. In addition, the weights between input data and feature nodes are initialized by SVD method, which avoids using iteration method to optimize them and also reduces computational cost. The experimental results on several regression datasets demonstrate that BLS with PSO and SVD can not only find optimal number of system nodes much faster than classical BLS but also achieve considerable satisfactory accuracy.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116858018","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}

引用次数: 0

Multi-pig Pose Estimation Using DeepLabCut 多猪姿态估计使用DeepLabCut

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642168

F. Farahnakian, J. Heikkonen, S. Björkman

{"title":"Multi-pig Pose Estimation Using DeepLabCut","authors":"F. Farahnakian, J. Heikkonen, S. Björkman","doi":"10.1109/ICICIP53388.2021.9642168","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642168","url":null,"abstract":"Pose estimation towards providing the assessments of animal health and welfare monitoring has strongly gained interest in the last few years. However, it is a challenging computer vision problem as the frequent interaction causes occlusions the association of detected key-points to the correct individuals. Deep Learning (DL) offers major advances in the field of pose estimation. In this paper, we investigated the possibility of using a famous open-source DL-based toolbox, DeepLabCut [1], for the specific pig pose estimation task. We predicted the body part of each individual pig from only input images or video sequences directly with no adaptations to the application setting. We used a real dataset which contains 2000 annotated images with 24,842 individually annotated pigs from 17 different locations and light conditions. The experimental results demonstrated that we can achieve a small root mean square error between the manual and predicted labels (10.1) when detecting pigs in environments previously seen by a DL model during training. To evaluate the robustness of the trained model, it is also tested on environments and lighting conditions unseen in the training set, where it achieves 12.0 root mean square error.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124889193","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}

引用次数: 2

Integrated Res2Net combined with Seesaw loss for Long-Tailed PCG signal classification 结合跷跷板损耗的综合Res2Net方法用于长尾PCG信号分类

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642156

Guangyang Tian, Cheng Lian, Zhigang Zeng

引用次数: 3

HINet: Hierarchical Point Cloud Frame Interpolation Network HINet:分层点云帧插值网络

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642217

Jiawen Xu, Zhiyuan You, Xinyi Le, Cailian Chen, X. Guan

{"title":"HINet: Hierarchical Point Cloud Frame Interpolation Network","authors":"Jiawen Xu, Zhiyuan You, Xinyi Le, Cailian Chen, X. Guan","doi":"10.1109/ICICIP53388.2021.9642217","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642217","url":null,"abstract":"Intelligent agents utilize various sensors such as LiDAR, cameras to perceive the surroundings. However, the frame rate difference among sensors seriously affects both safety and efficiency of intelligent agents. Recently some research concerning point cloud frame interpolation is conducted to solve the frame rate inconsistency problem by interpolating low frame rate point cloud sequences up to high frame rate ones. To improve the performance of current state-of-the-art method, we come up with a novel Hierarchical Point Cloud Frame Interpolation Network (HINet). By proposed hierarchical warping module, coarse intermediate frames are generated hierarchically to reach closer toward the target position. Besides, we propose spatial aware fusion strategy to hierarchically restore local geometric distribution by attention mechanism and positional offset. Finally, hierarchical supervision module is applied to efficiently train the HINet in two stages, guaranteeing the quality of predicted intermediate frames. We employ HINet in a large outdoor autonomous driving dataset and provide convincing qualitative and quantitative evaluation results.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129647609","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}

引用次数: 0

Epidemiology and Risk Factors of Scoliosis in College Students 大学生脊柱侧凸流行病学及危险因素分析

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642189

Jia-he Yang, J. Yi, Wenmei Li, Ting Zhang, Wei Liu, Xiaoling Duan

{"title":"Epidemiology and Risk Factors of Scoliosis in College Students","authors":"Jia-he Yang, J. Yi, Wenmei Li, Ting Zhang, Wei Liu, Xiaoling Duan","doi":"10.1109/ICICIP53388.2021.9642189","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642189","url":null,"abstract":"Poor posture and the overuse of electronic devices may lead to an increased incidence of spinal deformity and even scoliosis in students. To investigate the incidence of scoliosis in college students and to explore related risk factors for this problem, a cross-sectional study examining scoliosis was conducted with 318 college students and a cross-sectional survey was delivered to 593 college students on risk factors related to spinal health problems, after all a descriptive analysis and an analytic hierarchy process (AHP) were performed on the collected data. Among 318 college students, 7.23 % of them received a scoliosis diagnosis at greater than seven degrees. The results of the AHP showed that sitting with crossed legs was the most important risk factor for scoliosis. Among the 593 subjects, 35.92% of college students reported always sitting with crossed legs, 33.22% always falling asleep at their desk, and 79.59% seated for more than six hours per day. Spinal health problems, particularly scoliosis, are common among college students. Awareness should be spread for risk factors related to these problems.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124451279","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}

引用次数: 0

A BAS Algorithm Based Neural Network for Intrusion Detection 基于BAS算法的神经网络入侵检测

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642170

Pei Zhang, Yinyan Zhang

引用次数: 1

Gaze-driven Interaction System for Cognitive Ability Assessment 认知能力评估的注视驱动交互系统

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642161

Hanlin Zhang, Xinming Wang, Weihong Ren, Yuchen Zhao, Qingcai Chen, Jingyong Su, Junjie Chen, Honghai Liu

{"title":"Gaze-driven Interaction System for Cognitive Ability Assessment","authors":"Hanlin Zhang, Xinming Wang, Weihong Ren, Yuchen Zhao, Qingcai Chen, Jingyong Su, Junjie Chen, Honghai Liu","doi":"10.1109/ICICIP53388.2021.9642161","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642161","url":null,"abstract":"Autism Spectrum Disorder (ASD), usually discovered in childhood, is a neurodevelopmental disorder with clinical manifestations like social communication disorders, stereotyped behaviors, and narrow interests. Incomplete cognitive ability is one reason that causes social communication disorders among autistic children. Therefore, it is critical to evaluate the cognitive abilities of autistic children and provide guidance for subsequent intervention programs. In this work, we present a gaze-driven interaction system, assessing the cognitive performance of the subject. Based on our paradigms, an interface that contains specific pictures, videos and games creates a bond of interaction between subjects and the system. During the assessment process, the gaze features of subjects will be captured for deducing a cognitive ability index, which is used for judging the degree of cognition. The result shows that our system can evaluate the cognitive ability ranging from colors, shapes, emotions to social relationships, and provide guidance for the formulation of follow-up personalized intervention programs.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131018146","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}

引用次数: 0

Robot laser range controller design based on embedded technology 基于嵌入式技术的机器人激光测距控制器设计

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642195

Xin Li

引用次数: 0

Research on time series classification based on convolutional neural network with attention mechanism 基于注意机制的卷积神经网络时间序列分类研究

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642214

Debiao Li, Cheng Lian, Wei Yao

引用次数: 2

Diagnose of electronic circuits of the driver controller based on VPCA-BRB model 基于VPCA-BRB模型的驱动控制器电路诊断

2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2021-12-03 DOI: 10.1109/ICICIP53388.2021.9642221

Zhi Gao, Siyu Chen, Xinming Zhang, Bangcheng Zhang, Yubo Shao

{"title":"Diagnose of electronic circuits of the driver controller based on VPCA-BRB model","authors":"Zhi Gao, Siyu Chen, Xinming Zhang, Bangcheng Zhang, Yubo Shao","doi":"10.1109/ICICIP53388.2021.9642221","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642221","url":null,"abstract":"The controller of railway vehicle is the main command control electric appliance which controls the operation of railway vehicle. Any fault of the electronic circuit of the controller will cause the safety accident of railway vehicle. Aiming at the problem of low accuracy in fault diagnosis of controller electronic circuits caused by fuzzy meaning in feature extraction, a fault diagnosis method based on maximum variance rotating principal component analysis and confidence rule base was proposed. Firstly, the dimensionality of the data was reduced by the principal component analysis of the maximum variance rotation to improve the explan ability of the factors after dimensionality reduction. Then the belief rule base reasoning method based on evidence reasoning was used to diagnose the fault, and the CMA-E algorithm was used to optimize the initial parameters of the established model, so as to improve the accuracy of fault diagnosis of electronic circuit of railway vehicle. The effectiveness of the proposed method is verified by simulation and experiment.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124270737","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}

引用次数: 0