机译:基于稀疏表示的瓶盖表面缺陷快速检测方法
Shanghai Key laboratory of Power Station Automation Technology, School of Mechatronical Engineering and Automation, Shanghai University, Shanghai 200072, China,School of Information and Electronic Engineering, Ludong University, Yantai 264025, China,UK-China Science Bridge Joint Laboratory, Shanghai University, Shanghai, China,UK-China Science Bridge Joint Laboratory, Queen's University Belfast, UK;
Shanghai Key laboratory of Power Station Automation Technology, School of Mechatronical Engineering and Automation, Shanghai University, Shanghai 200072, China,UK-China Science Bridge Joint Laboratory, Shanghai University, Shanghai, China,UK-China Science Bridge Joint Laboratory, Queen's University Belfast, UK;
School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast BT9 5 AH, UK;
School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast BT9 5 AH, UK,UK-China Science Bridge Joint Laboratory, Shanghai University, Shanghai, China,UK-China Science Bridge Joint Laboratory, Queen's University Belfast, UK;
Fast detection; Bottle cap; Surface defect; Circular region projection histogram (CRPH); Sparse representation;
机译:基于低秩和稀疏表示的视觉表面缺陷检测方法
机译:具有堆叠稀疏自动编码器和卷积神经网络的深度特征表示,用于基于高光谱成像的黄瓜缺陷检测
机译:具有堆叠稀疏自动编码器和卷积神经网络的深度特征表示,用于基于高光谱成像的黄瓜缺陷检测
机译:基于机器视觉的管型瓶表面缺陷检测算法研究
机译:在纹理表面上基于视觉的缺陷检测算法。
机译:基于深卷积神经网络的轨道表面和紧固件缺陷检测方法
机译:通过L2稀疏表示快速混凝土裂纹检测方法