Paper Publications

• [1] Crowd counting network based on attention feature fusion and multi-column feature enhancement.Journal of Visual Communication and Image Representation.2024,105:104323
• [2] Double multi-scale feature fusion network for crowd counting.Multimedia Tools and Applications.2024,83(34):81831-81855
• [3] Double reuses based residual network.Neurocomputing.2024,593:127803
• [4] Gated feature aggregate and alignment network for real-time semantic segmentation of street scenes.Multimedia Systems.2024,30(4):213
• [5] Deep network with double reuses and convolutional shortcuts.IET Computer Vision.2024,18(4):512-525
• [6] Attention based lightweight asymmetric network for real-time semantic segmentation.Engineering Applications of Artificial Intelligence.2024,130:107736
• [7] Multi-scale cross-layer fusion and center position network for pedestrian detection.Journal of King Saud University - Computer and Information Sciences.2024,36(1):101886
• [8] Attribute Feature Fusion Network for Pedestrian Detection and Re-Identification.International Conference on Robotics and Computer Vision (ICRCV).2023:36-40
• [9] Semi-supervised uncorrelated dictionary learning for colour face recognition.IET Computer Vision.2020,14(3):92-100
• [10] Within-component and Between-component Multi-kernel Discriminating Correlation Analysis for Colour Face Recognition.IET Computer Vision.2017,11(8):663-674
• [11] Dual Multi-kernel Discriminant Analysis for Color Face Recognition.Optik.2017,139:185-201
• [12] Kernel Local Sparse Representation Based Classifier.Neural Processing Letters.2016,43(1):85-95
• [13] Parallel Nonlinear Discriminant Feature Extraction for Face and Handwritten Digit Recognition.Lecture Notes in Computer Science (Chinese Conference on Biometric Recognition, CCBR).2015,9428:536-543
• [14] Colour-feature dual discriminating correlation analysis for face recognition.IET Computer Vision.2015,9(4):467-475
• [15] Within-component and Between-component Discriminant Analysis for Color Face Recognition.Optik.2014,125(21):6366-6374