A5102631011- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Infrared Target Detection Methodologies
- Gait Recognition and Analysis
- AI in cancer detection
- Automated Road and Building Extraction
- Face recognition and analysis
- Impact of Light on Environment and Health
- Radiomics and Machine Learning in Medical Imaging
- Human Pose and Action Recognition
Jiangsu University of Science and Technology
2024-2025
Visible-infrared person re-identification (VI-ReID) task is to retrieve the same pedestrian across visible and infrared modalities. The existing transformer-based works are constrained by inherent structure of ViT that feature collapse in deeper layers over-globalization extracted features, resulting incomplete learning local low-level features. However, these features instrumental representing identifying elements within visible-infrared images more comprehensively, which increases accuracy...
Due to target diversity, life-cycle variations, and complex backgrounds, traditional pest detection methods often struggle with accuracy efficiency. This study introduces RDW-YOLO, an improved algorithm based on YOLO11, featuring three key innovations. First, the Reparameterized Dilated Fusion Block (RDFBlock) enhances feature extraction via multi-branch dilated convolutions for fine-grained characteristics. Second, DualPathDown (DPDown) module integrates hybrid pooling convolution better...
Accurate medical image segmentation can assist doctors in observing lesion areas and making precise judgments. Effectively utilizing important multi-scale semantic information local global contexts is key to improving accuracy. In this paper, we present a dual attention network (MSDA-Net), which enhances feature representation under different receptive fields effectively utilizes the from both images. MSDA-Net typical encoder–decoder structure introduces multi-receptive field densely...
Two-dimensional human pose estimation aims to equip computers with the ability accurately recognize keypoints and comprehend their spatial contexts within media content. However, accuracy of real-time diminishes when processing images occluded body parts or overlapped individuals. To address these issues, we propose a method based on YOLO framework. We integrate convolutional concepts Kolmogorov–Arnold Networks (KANs) through introducing non-linear activation functions enhance feature...
The main challenge in the Visible-Infrared Person Re-Identification (VI-ReID) task lies how to extract discriminative features from different modalities for matching purposes. While existing well works primarily focus on minimizing modal discrepancies, modality information can not thoroughly be leveraged. To solve this problem, a Multi-scale Semantic Correlation Mining network (MSCMNet) is proposed comprehensively exploit semantic at multiple scales and simultaneously reduce loss as small...
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