2022 4th International Conference on Robotics and Computer Vision (ICRCV)最新文献_第7页

Detection Capability Analysis for AWACS Based on the Doppler Blind Zone Map 基于多普勒盲区图的预警机探测能力分析

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-09-25 DOI: 10.1109/ICRCV55858.2022.9953237

Mao Zheng, Hui Zhang, W. Wu, Weiping Huang

引用次数: 0

Vector Control Technology of Two-Phase Hybrid Stepping Motor Based on Current Loop PI Regulator 基于电流环PI调节器的两相混合式步进电机矢量控制技术

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-09-25 DOI: 10.1109/ICRCV55858.2022.9953224

Ming Fu, Quan Ran

引用次数: 0

CART Decision Tree Based Human State Estimation Algorithm and Research 基于CART决策树的人体状态估计算法与研究

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-09-25 DOI: 10.1109/ICRCV55858.2022.9953220

Rongfei Ma, Wenxia Xu, Baocheng Yu, Min Zhang, Jing Wu, Huizhi Zhu

{"title":"CART Decision Tree Based Human State Estimation Algorithm and Research","authors":"Rongfei Ma, Wenxia Xu, Baocheng Yu, Min Zhang, Jing Wu, Huizhi Zhu","doi":"10.1109/ICRCV55858.2022.9953220","DOIUrl":"https://doi.org/10.1109/ICRCV55858.2022.9953220","url":null,"abstract":"Human state estimation is an important technical tool in the field of elderly mobility assistance. In order to further improve the accuracy of human state recognition, a CART decision tree based human state classification algorithm was proposed for the auxiliary support system. Firstly, the human inertial sensor posture data was pre-processed, the human body link model was used to calculate the human body center of gravity for posture detection of sitting and standing motion process, extract features and training samples, then the dimensionality of the posture data was reduced by PCA method to get the best subset of data with good reflection of human body posture, the motion process includes four consecutive states: sitting, rising, standing and falling, and the state transition stages were subdivided into another four categories, and finally the CART decision tree algorithm was used to train the samples to generate CART rule trees to classify the human posture. The experimental results show that the classification accuracy of the human posture detection system under the constructed CART decision tree is up to 98%, which is better than the SVM classification results, and the estimation is correct in the vicinity of the state transition, and the accuracy of the state estimation is reasonable.","PeriodicalId":399667,"journal":{"name":"2022 4th International Conference on Robotics and Computer Vision (ICRCV)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127643542","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

Airplane Object Detection in Satellite Images Based on Attention Mechanism and Multi-scale Feature Fusion 基于注意机制和多尺度特征融合的卫星图像飞机目标检测

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-09-25 DOI: 10.1109/ICRCV55858.2022.9953228

Zhiwei Xia, Jun Liu, Xiao Chen, Xin Li, Peng Chen

{"title":"Airplane Object Detection in Satellite Images Based on Attention Mechanism and Multi-scale Feature Fusion","authors":"Zhiwei Xia, Jun Liu, Xiao Chen, Xin Li, Peng Chen","doi":"10.1109/ICRCV55858.2022.9953228","DOIUrl":"https://doi.org/10.1109/ICRCV55858.2022.9953228","url":null,"abstract":"The order of magnitude of object detection instances in satellite images is larger than that in conventional images, and many small object instances are clustered together in satellite images. Most objects in conventional object detection datasets are perpendicular to the ground, while objects in satellite images are parallel to the ground and their orientation varies greatly. Conventional detection with horizontal bounding box, a horizontal bounding box may contain multiple dense instances and may contain a lot of background information, resulting in a disproportionate proportion of the background in the detection box. The oriented bounding box helps to locate the object more accurately and obtain the azimuth information of the object more easily. Therefore, in this work, we used oriented bounding boxes to detect airplane objects in satellite images. In order to target the detection of airplane objects, we produced a high-resolution dataset containing only airplane objects and more small instances. We use ResNet as backbone and FPN as Neck. By adding an SE Block module after each stage of ResNet to pay attention to important features, and connecting a pyramid convolution (PConv) module after FPN to enhance feature fusion. Cropping the input image to 1024*1024 using a sliding window allowed detection accuracy improved on DOTA v1.0(90.53 mAP) and our own dataset Satellite-Airplane2309(83.48 mAP) on the GTX TITAN X.","PeriodicalId":399667,"journal":{"name":"2022 4th International Conference on Robotics and Computer Vision (ICRCV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132105018","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

Research on Human-in-the-loop Traffic Adaptive Decision Making Method 人在环路交通自适应决策方法研究

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-09-25 DOI: 10.1109/ICRCV55858.2022.9953216

Peng Zhang, Wei Liu, Junjie Shao

{"title":"Research on Human-in-the-loop Traffic Adaptive Decision Making Method","authors":"Peng Zhang, Wei Liu, Junjie Shao","doi":"10.1109/ICRCV55858.2022.9953216","DOIUrl":"https://doi.org/10.1109/ICRCV55858.2022.9953216","url":null,"abstract":"Most intelligent transportation systems, such as driverless cars and drones, try to reduce people’s participation and realize intelligent transportation. However, the lack of human participation will lead to the weak adaptive ability of intelligent transportation systems, which can't cope with emergencies and other problems. In response to this situation, this paper introduces the adaptive decision-making method of human-in-the-loop. Firstly, the agent is trained by introducing human feedback into the traditional reinforcement learning algorithm. Through the interaction between agents with the environment and humans, the process of \"exploration-learning-decision making\" is repeated constantly, accumulating experience and optimizing strategies in the process of interacting with the environment and humans. The agent continuously updates the decision-making process through human feedback and can avoid static obstacles and dynamic obstacles in the environment, finally reach the target point. Secondly, the human-in-the-loop algorithm of DQN-TAMER is put forward, and experiments are carried out through three groups of human-in-the-loop algorithms. The experimental results show that the self-adaptive decision-making method of human-in-the-loop traffic can obviously improve the decision-making ability of intelligent transportation systems and the adaptability of the whole system, and the learning efficiency of agents is significantly improved by DQN-TAMER's human-in-the-loop algorithm. Finally, the medical material transportation simulation system is used as a prototype.","PeriodicalId":399667,"journal":{"name":"2022 4th International Conference on Robotics and Computer Vision (ICRCV)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130631444","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

Semi-supervised Labeling Model Based on Gaussian Mixture in the Context of E-commerce Price Fraud 电子商务价格欺诈中基于高斯混合的半监督标注模型

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-09-25 DOI: 10.1109/ICRCV55858.2022.9953227

Jing Wang, Jun Liu, Zhiwei Xia, Peng Chen, Xin Li, Xiao Chen

引用次数: 0

Environmental Sound Detection based on Acoustic Multidimensional Synergistic Features and MobileNet-EAL 基于声学多维协同特征和MobileNet-EAL的环境声检测

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-09-25 DOI: 10.1109/ICRCV55858.2022.9953214

Baocheng Yu, Chuyuan Liao, Wenxia Xu, Ming Wei, Canjiong Lv, Jiaxin Li

{"title":"Environmental Sound Detection based on Acoustic Multidimensional Synergistic Features and MobileNet-EAL","authors":"Baocheng Yu, Chuyuan Liao, Wenxia Xu, Ming Wei, Canjiong Lv, Jiaxin Li","doi":"10.1109/ICRCV55858.2022.9953214","DOIUrl":"https://doi.org/10.1109/ICRCV55858.2022.9953214","url":null,"abstract":"For the problem of environmental sound detection in complex environments, the environmental sound detection method based on acoustic multidimensional synergistic features and MobileNet-EAL is proposed. Firstly, the acoustic multidimensional synergistic features of the input audios are extracted to achieve the complementary frequency and time domain information, the complementary static and dynamic information to enhance the ability to express the temporal characteristics of the sound signal. Secondly, the ECA_Net channel attention mechanism is added to the MobileNet-EAL network model proposed to make the model ignore the influence and interference caused by the background sound. Meanwhile, the Leaky ReLU activation function is also used to enhance the model's extraction of negative audio feature information to achieve sound detection in complex environments. The experimental results show that the classification accuracy reaches 91.4% on the UrbanSound8K dataset. Compared with traditional environmental sound recognition methods, the method adopted in this paper has obvious advantages in recognition rate and recognition efficiency.","PeriodicalId":399667,"journal":{"name":"2022 4th International Conference on Robotics and Computer Vision (ICRCV)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132995026","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

Recognising Known Configurations of Garments For Dual-Arm Robotic Flattening 双臂机器人展平中已知服装构型的识别

2022 4th International Conference on Robotics and Computer Vision (ICRCV) Pub Date : 2022-04-30 DOI: 10.1109/ICRCV55858.2022.9953186

Li Duan, G. Aragon-Camarasa

引用次数: 1