1 State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 2 University of Chinese Academy of Sciences, Beijing, China 3 School of Information Science and Engineering, Shenyang University of Chemical Technology, Shenyang, China Recently, electroencephalogram (EEG) based on motor imagery (MI) have gained significant traction in brain-computer interface (BCI) technology, particularly for the rehabilitation of paralyzed patients. But the low signal-to-no

Shun Yao 1 * Yihan Ping 2 Xiaoyu Yue 3,4 He Chen 3,4 1 Department of Public Instruction, ChangJiang Polytechnic of Art and Engineering, Jingzhou, China 2 School of Computer Science, Northwestern University, Evanston, IL, United States 3 School of Physical Education, Hubei University of Science and Technology, Xianning, China 4 College of Physical Education, Sangmyung University, Seoul, Republic of Korea Introduction: Accurate recognition of martial arts leg poses is essential for applications in sports

1 School of Foreign Languages, Henan Polytechnic University, Jiaozuo, China 2 College of Foreign Languages, Wenzhou University, Wenzhou, China Introduction: Emotion detection in written text is critical for applications in human-computer interaction, affective computing, and personalized content recommendation. Traditional approaches to emotion detection primarily leverage textual features, using natural language processing techniques such as sentiment analysis, which, while effective, may miss subtle

Autonomous driving is one of the hallmarks of arIficial intelligence. Neuromorphic, brain-inspired compuIng architectures, are revoluIonizing vehicular auton…

1 College of Artificial Intelligence, Taiyuan University of Technology, Jinzhong, Shanxi, China 2 Business School of Northeast Normal University, Northeast Normal University, Changchun, Jilin, China 3 College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Jinzhong, Shanxi, China Accurate building segmentation has become critical in various fields such as urban management, urban planning, mapping, and navigation. With the increasing diversity in the number, size, and shape of

1 School of Computer Science, Northwestern Polytechnical University, Xi’ an, China 2 School of Computer Science and Technology, Xi’ an University of Posts and Telecommunications, Xi’ an, Shaanxi, China 3 School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’ an, China Significant strides have been made in emotion recognition from Electroencephalography (EEG) signals. However, effectively modeling the diverse spatial, spectral, and temporal features

1 Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan, China 2 Kunming Cigarette Factory, Hongyunhonghe Tobacco Group Company Limited, Kunming, Yunnan, China Existing image fusion methods primarily focus on complex network structure designs while neglecting the limitations of simple fusion strategies in complex scenarios. To address this issue, this study proposes a new method for infrared and visible image fusion based on a multimodal large

Sports Department of Zhejiang A & F University, Hangzhou, Zhejiang, China Introduction: In recent years, with advancements in wearable devices and biosignal analysis technologies, sports performance analysis has become an increasingly popular research field, particularly due to the growing demand for real-time monitoring of athletes’ conditions in sports training and competitive events. Traditional methods of sports performance analysis typically rely on video data or sensor data for motion recognition.

Department of Information Engineering, Shanghai Maritime University, Shanghai, China Introduction: RGB-T Salient Object Detection (SOD) aims to accurately segment salient regions in both visible light and thermal infrared images. However, many existing methods overlook the critical complementarity between these modalities, which can enhance detection accuracy. Methods: We propose the Edge-Guided Feature Fusion Network (EGFF-Net), which consists of cross-modal feature extraction, edge-guided feature