Newly accepted

• Jia Zhang , Bo Peng et al. CLIP Graph Adaptor: A Dual-Graph Adapted Visual–Language Model for Weakly Supervised Semantic Segmentation. IEEE  Transactions on Neural Networks and Learning Systems. 2026
  

• Kunlun Wu, Bo Peng, Donghai Zhai. Spatiotemporal Context-Aware Prompting with Low-Rank Dynamic  Routing for Exemplar-free Video Class-Incremental Learning. IEEE Transactions on Neural Networks and  Learning Systems. 2026 DOI: 10.1109/TNNLS.2026.3698473
  

• Zaid Al-Huda, Bo Peng et al. global and local encoder fusion network for pavement crack segmentation. Applied Soft Computing, 201,115497, 2026.
  

• Tingyu Zhao, Bo Peng et al. HSSN: Hierarchical Superpixel Segmentation Network Guided by Visual Attention Mechanism. Signal processing. 239:110332, 2026.
  

• Daipeng Yang, Bo Peng, Tingyu Zhao, Xiaofan Li. A regular superpixel generation method based on continuous edges. Signal Processing. 241, 110412,2026.
  

  
  

代表性论文：

• Jia Zhang, Bo Peng*, et al.  CDGR: Cross-Modal Dual Graph Reasoning for Weakly Supervised Semantic Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. 36(2):1668 - 1680, 2025 [paper] DOI: 10.1109/TCSVT.2025.3602416

• Jia Zhang, Bo Peng*, Xi Wu.  Dual Graph Inference Network for Weakly Supervised Semantic Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. 35(8):8104 - 8118, 2025.  [paper][code] DOI: 10.1109/TCSVT.2025.3544331

• Zhenguang Zhang, Bo Peng*, et al. , An ultra-lightweight network combining Mamba and frequency-domain feature extraction for pavement tiny-crack segmentation. Expert Systems With Applications. 264:125941, 2025. [paper]

• Kunlun Wu, Bo Peng, et al. Boundary-aware Axial Attention Network for High-quality Pavement Crack Detection. IEEE Transactions on Neural Networks and Learning Systems. 2024. [paper]

• Jia Zhang, Bo Peng*, et al. Weakly Supervised Semantic Segmentation by Knowledge Graph Inference. Engineering Applications of Artificial Intelligence.  138,109294, 2024 [paper]

• Zhenguang Zhang, Zaid Al-Huda, Bo Peng*, Jie Hu. A bio-inspired network with automatic brightness adaptation for pavement crack detection in different environments. IEEE Transactions on Instrumentation and Measurement. 73, 5035715, 2024 [paper]
  

• Xiaofan Li, Bo Peng*, et al., Difficult Airway Assessment with Multi-View Contrastive Representation Prior and Ensemble Classification. Biomedical Signal Processing and Control. (98):106738, 2024. [paper]
  

• Omar Al-maqtari, Bo Peng* et al. Transformer-Based Thin Crack Segmentation: An Efficient Multiscale Approach for Automatic Visual Inspection. Signal, Image and Video Processing. 2024. [paper][code]

• Daipeng Yang, Bo Peng*, Xi Wu. A bio-inspired edge and segment detection method by modeling multiple visual regions.  Visual Computer. 2024. [paper][code]
  

• Mingxu Li, Bo Peng, et al., Latent Space Segmentation model for Visual Surface Defect Inspection. IEEE Transactions on Instrumentation and Measurement. 2024. [paper]

• Peng Huang, Shu Hu, Bo Peng, et al. Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases Detection. MICCAI 2024.  [paper][code] (CCF B类会议)
  

• Omar Al-maqtari, Bo Peng* et al. Lightweight Yet Effective: A Modular Approach to Crack Segmentation. IEEE Transactions on Intelligent Vehicles. 2024. [paper] [code] (IF: 14) 
  

• Tingyu Zhao, Bo Peng*, et al. Rethinking Superpixel Segmentation from Biologically Inspired Mechanisms. Applied Soft Computing. 156: 111467, 2024. [paper][code] (IF: 7.2)

• Xiaofan Li，Bo Peng*，et al. USL-Net: Uncertainty Self-Learning Network for Unsupervised Skin Lesion Segmentation, Biomedical Signal Processing and Control. 89,105769, 2024 [paper](IF: 4.9)
  

• Zaid Al-Huda, Bo Peng*, et al. Asymmetric Dual-Decoder-U-Net for Pavement Crack Semantic Segmentation. Automation in Construction. 156,105138, 2023 (IF: 10.3)

• Zaid Al-Huda, Bo Peng*, et al. A Hybrid Deep Learning Pavement Crack Semantic Segmentation. Engineering Applications of Artificial Intelligence. 122, 106142, 2023. (ESI 热点论文)

更多请见(按时间顺序)  https://dblp.uni-trier.de/pid/03/5954-6.html

计算机视觉：图像识别与分割、生物视觉低层图像处理技术

机器学习技术：弱监督和自监督学习、图学习、跨域学习

人工智能技术应用：图像语言大模型，生成式大模型，基于深度学习的医学诊断、道路工程缺陷检测

暂无内容

暂无内容