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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Zhu, Yongchang Dong, Enzeng Tong, Jigang Yang, Sen Zhang, Zufeng Li, Wenyu Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory 391 Binshui West Road Tianjin China Nankai University College of Artificial Intelligence 94 Weijin Road Tianjin China

ISBN: (纸本)9798350320831

Target detection is a significant research direction in the realm of computer vision, aimed at analyzing and localizing targets in input images to obtain their categories and locations. However, this task is faced with several challenges in complex scenarios, such as large variations in target scales, similarity to the background, dense number, and overlapping with each other, making it difficult for the target detection model to extract different scales and discriminative target features adaptively, leading to low detection accuracy and weak generalization ability. To tackle the aforementioned problems, this study proposes a novel approach by optimizing the detection head of the model, invoking decoupled detection heads, dividing the classification and localization tasks, and optimizing for small targets. This approach effectively reduces the false detection rate and the missed detection rate, enabling the network to better discriminate and recognize distant objects as well as objects of relatively small size. Moreover, the proposed approach outperforms the yolov7 model by 0.8% in the COCO dataset, not only improving the accuracy of detecting distant and small targets but also exhibiting better performance in conventional target detection. Additionally, this approach is capable of handling small targets, overlapping targets, or relatively dense targets, significantly expanding its practical use range. © 2023 IEEE.

关键词： Object detection

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Design of Visual Gaze Target Locating Device Based on Depth Camera

Design of Visual Gaze Target Locating Device Based on Depth ...

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IEEE International Conference on Computational intelligence and Virtual Environments for Measurement Systems and Applications

作者： Yuxin. Liu Lintao. Hu Bowen. Xiao Xiao Y. Wu Yanhan. Chen Donghai. Ye Wen S. Hou Xiaolin. Zheng Key Laboratory of Biorheological Science and Technology of Ministry of Education & Collaborative Innovation Center for Brain Science Chongqing University Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology College of art Chongqing University Chongqing China Chongqing Medical Electronics Engineering Technology Research Center

ISBN: (数字)9781538683446

ISBN: (纸本)9781538683453

Based on the research of machine vision positioning application in recent years, this paper discusses the common machine vision positioning system and its principle, and designs a visual target positioning device to detect people's target intention. It mainly includes dynamic following and target positioning functions. Dynamic following can determine the fixation direction of the tester, and target positioning can obtain the spatial position information of the fixation target. The device can recognize the intention of people by observing the visual fixation direction of the subject and obtain the spatial position information of the target, which is a human-computer interaction path with a widely used scene.

关键词： Cameras Visualization Neck Microprocessors Target recognition Head

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Beta Changes Induced by Acute Hand Loss Model during NMES *

Beta Changes Induced by Acute Hand Loss Model during NMES *

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Yun Zhao Guang H. Xie Ren Q. Yang Hai Y. Qin Yu P. Yang Xiao Y. Wu Wen S. Hou School of Smart Health Chongqing College of Electronic Engineering and the Key Laboratory of Biorheological Science and Technology Ministry of Education Chongqing University Chongqing China School of Smart Health Chongqing College of Electronic Engineering Chongqing China The Chongqing Medical Electronics Engineering Technology Research Center and the Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology Key Laboratory of Biorheological Science and Technology Ministry of Education Chongqing University Chongqing China

Neuromuscular electrical stimulation (NMES) has been demonstrated to effectively modulate cortical activities by evoking muscle contraction in upper limb and generating joint movements, which showed an excellent performance in motor rehabilitation. However, due to hand loss and cortical function reorganization induced by hand amputation, how neural activities in sensorimotor cortex response to NMES-evoked muscle contraction in the end of an amputation stump is not clear. In this paper, Ischemic nerve block (INB) technique was used to build an acute hand loss model, and 64-channel EEG signals were recorded from 11 healthy subjects to perform a 2×2 factorial design protocol, with the INB state and the current intensity as factors. The changes of NMES-evoked sensorimotor cortical activities were quantified by computing Beta-band event-related desynchronization (Beta ERD) patterns and the time-varying functional connectivity using adaptive directed transfer function (ADTF) before and during INB. The acute hand "loss" resulted in ipsilateral dominance of Beta ERD induced by NMES with two current intensities in the topographic maps, that is, ipsilateral Beta ERD was significantly higher than that the contralateral one (p<0.05). However, before INB, Beta ERD in the contralateral sensorimotor cortex induced by NMES above motor threshold was significantly higher than that in the ipsilateral area (p< 0.01). Meanwhile, whatever before or during INB, clustering coefficients of the ADTF network in sensorimotor cortex showed temporal dynamics during two NMES tasks. During INB, NMES above motor threshold-evoked lower clustering coefficients of the time-varying network in sensorimotor cortex than that before INB (p<0.05). The present results suggest that the loss of the hand proprioception will degrade cortical activities in the contralateral area, and increase cortical activities in the ipsilateral area compensatively responding to NMES. This finding may be particularly important

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Spectroscopic techniques combined with DD-SIMCA model and explainable artificial intelligence for rapidly and accurately identifying the quality of Astragali Radix

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Industrial Crops and Products 2025年 231卷

作者： Bai, Lei Zhang, Zhi-Tong Yuan, Dongping Hu, Ziliang Qi, Yali Liu, Wenjian Guan, Huanhuan Chen, Li Shi, Zhiqi Hu, Chenjun Xue, Mei Li, Jindong Yan, Guojun State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Nanjing University of Chinese Medicine Nanjing210023 China Taizhou School of Clinical Medicine The Affiliated Taizhou People's Hospital of Nanjing Medical University Taizhou225300 China Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine Wuxi214071 China School of Artificial Intelligence and Information Technology Nanjing University of Chinese Medicine Jiangsu Province Engineering Research Center of TCM Intelligence Health Service Nanjing210023 China

Astragali Radix (AR) is a traditional Chinese medicine (TCM) widely used worldwide for its nutritional and medicinal benefits, but it is facing increasing quality issues. This article developed a novel method for quickly and accurately identifying AR's quality. In this study, spectroscopic techniques combined with data-driven soft independent modelling of class analogy (DD-SIMCA) and explainable artificial intelligence (XAI) were used to determine AR's geographic origins and predict its antioxidant activity. The results showed that preprocessed near-infrared (NIR) or raw visible (VIS) spectra with DD-SIMCA could accurately identify AR's authentic regions, with 100 % sensitivity, specificity, and accuracy. Additionally, XAI identified 80 features from NIR spectra and 33 from VIS spectra, both strongly correlated with AR's antioxidant activity. Fusing these features and integrating them with support vector machine led to significantly better model performance, with Rp2 of 0.9760, RPDP of 6.7447, RMSEP of 1.3824, and MAEP of 1.1088. Overall, this study provided valuable insights for the quality assessment of TCMs and other medicinal plants. © 2025 The Authors

关键词： Damage detection

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Research on the treatment method of COVID-19 sequelae with intelligent soft manipulator based on haptic feedback

Research on the treatment method of COVID-19 sequelae with i...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Huang, Zixin Li, Xinpeng Deng, Jie Li, Yun Wan, Xiao Wang, Lejun Nankai University School of Electrical and Information Engineering Wuhan Institute of Technology Collage of Artificial Intelligence China Wuhan Institute of Technology School of Electrical and Information Engineering Wuhan China Hubei University of Chinese Medicine Hubei Provincial Hospital of Traditional Chinese Medicine Wuhan China Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing China

ISBN: (纸本)9798350327182

Soft manipulator has the advantages of high degree of freedom, strong adaptability, high safety, good man-machine interaction ability, and has a wide range of application prospects in the medical field. In the treatment of traditional Chinese medicine, acupoint therapy can effectively treat diseases and avoid the side effects of drug therapy. Acupoint therapy can be used to treat the sequelae of the elderly in the post-COVID-19 era. Inspired by this, this paper designs and produces an intelligent soft manipulator. Such manipulator can realize the function of acupoint physiotherapy for part of human body through the pressure drive, and realize the real-time feedback function through the sensor to feedback the pressure signal to the upper position machine. Such manipulator provides a feasible treatment method for the sequelae of COVID-19 through physical therapy. © 2023 IEEE.

关键词： COVID-19

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CPTNet: Cascade Pose Transform Network for Single Image Talking Head Animation 15th

CPTNet: Cascade Pose Transform Network for Single Image Talk...

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15th Asian Conference on Computer Vision, ACCV 2020

作者： Zhang, Jiale Xian, Ke Liu, Chengxin Chen, Yinpeng Cao, Zhiguo Zhong, Weicai Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Huawei CBG Consumer Cloud Service Search Product and Big Data Platform Department Xi’an China

ISBN: (纸本)9783030695378

We study the problem of talking head animation from a single image. Most of the existing methods focus on generating talking heads for human. However, little attention has been paid to the creation of talking head anime. In this paper, our goal is to synthesize vivid talking heads from a single anime image. To this end, we propose cascade pose transform network, termed CPTNet, that consists of a face pose transform network and a head pose transform network. Specifically, we introduce a mask generator to animate facial expression (e.g., close eyes and open mouth) and a grid generator for head movement animation, followed by a fusion module to generate talking heads. In order to handle large motion and obtain more accurate results, we design a pose vector decomposition and cascaded refinement strategy. In addition, we create an anime talking head dataset, that includes various anime characters and poses, to train our model. Extensive experiments on our dataset demonstrate that our model outperforms other methods, generating more accurate and vivid talking heads from a single anime image. © 2021, Springer Nature Switzerland AG.

关键词： Animation

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Time-varying group formation-tracking control for heterogeneous multi-agent systems with switching topologies and time-varying delays

Time-varying group formation-tracking control for heterogene...

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第40届中国控制会议

作者： Shiyu Zhou Xiaobao Wei Xiwang Dong Yongzhao Hua Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education of ChinaChongqing University Institute of Artificial Intelligence Beihang University

Group formation-tracking problem for heterogeneous multi-agent systems（HMASs） with both switching networks and communication delays is investigated in this paper. In order to achieve different tasks, the agents are classified into various groups. The followers are allowed to realize the formation and track the trajectory of the leader in each group. Firstly, by utilizing the consensus control, an observer is proposed to estimate the state of the leader. Then, an observer-based control protocol is put forward to solve the group formation-tracking problem with both communication delays and switching networks. Moreover, an algorithm to determine the gain feedbacks is demonstrated, in the meantime, the observer’s error systems as well as the group formation-tracking error systems are proved to be convergent. Finally, an example in the simulation prat is presented to verify the theoretical results.

关键词： Group formation-tracking problem general linear multi-agent systems time-varying delays switching topologies

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DisGNet: A Distance Graph Neural Network for Forward Kinematics Learning of Gough-Stewart Platform

arXiv

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arXiv 2024年

作者： Zhu, Huizhi Xu, Wenxia Huang, Jian The Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan430205 China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

In this paper, we propose a graph neural network, DisGNet, for learning the graph distance matrix to address the forward kinematics problem of the Gough-Stewart platform. DisGNet employs the k-FWL algorithm for message-passing, providing high expressiveness with a small parameter count, making it suitable for practical deployment. Additionally, we introduce the GPU-friendly Newton-Raphson method, an efficient parallelized optimization method executed on the GPU to refine DisGNet’s output poses, achieving ultra-high-precision pose. This novel two-stage approach delivers ultra-high precision output while meeting real-time requirements. Our results indicate that on our dataset, DisGNet can achieves error accuracys below 1mm and 1deg at 79.8% and 98.2%, respectively. As executed on a GPU, our two-stage method can ensure the requirement for real-time computation. Codes are released at https://***/FLAMEZZ5201/DisGNet. Copyright © 2024, The Authors. All rights reserved.

关键词： Newton-Raphson method

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Step-by-Step: controlling Arbitrary Style in Text with Large Language Models 30

Step-by-Step: Controlling Arbitrary Style in Text with Large...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liu, Pusheng Wu, Lianwei Wang, Linyong Guo, Sensen Liu, Yang National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University China Research & Development Institute of Northwestern Polytechnical University Shenzhen China Chongqing Science & Technology Innovation Center of Northwestern Polytechnical University China State Key Laboratory of Integrated Service Networks Xidian University China School of Artificial Intelligence Optics and Electronics Northwestern Polytechnical University China

ISBN: (纸本)9782493814104

Recently, the autoregressive framework based on large language models (LLMs) has achieved excellent performance in controlling the generated text to adhere to the required style. These methods guide LLMs through prompt learning to generate target text in an autoregressive manner. However, this manner possesses lower controllability and suffers from the challenge of accumulating errors, where early prediction inaccuracies might influence subsequent word generation. Furthermore, existing prompt-based methods overlook specific region editing, resulting in a deficiency of localized control over input text. To overcome these challenges, we propose a novel three-stage prompt-based approach for specific region editing. To alleviate the issue of accumulating errors, we transform the text style transfer task into a text infilling task, guiding the LLMs to modify only a small portion of text within the editing region to achieve style transfer, thus reducing the number of autoregressive iterations. To achieve an effective specific editing region, we adopt both prompt-based and word frequency-based strategies for region selection, subsequently employing a discriminator to validate the efficacy of the selected region. Experiments conducted on several publicly competitive datasets for text style transfer task confirm that our proposed approach achieves state-of-the-art performance. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

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Deep Neural Network Based Object Detection Algorithm With optimized Detection Head for Small Targets

Deep Neural Network Based Object Detection Algorithm With op...

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IEEE International Conference on Mechatronics and Automation

作者： Yongchang Zhu Enzeng Dong Jigang Tong Sen Yang Zufeng Zhang Wenyu Li Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology 391 Binshui West Road Tianjin China College of Artificial Intelligence Nankai University 94 Weijin Road Tianjin China

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