computer vision; feature extraction; image classification; image representation; image segmentation; bioinspired model; biological neural vision mechanism; biological vision systems; complex neural layers; feature detection; figure-ground separation; ganglion cell; human-made machine vision systems; image classification tasks; image segmentation; image semantics; local feedback control circuit; neural model; nonclassical receptive fields; nontask-dependent image representation schema; object recognition; pixel level; Biological system modeling; Image reconstruction; Image representation; Mathematical model; Radio frequency; Semantics; Shape; bio-inspired model; early vision; image representation;
机译:基于非经典感受野的基础设施图像表示
机译:盲S3D使用经典和非古典接收场模型预测
机译:基于非经典感受野的多尺度集成轮廓检测模型
机译:基于非古典接受领域的图像表示的生物启发模型
机译:感受野散射的计算用途:稀疏的图像表示,快速的非线性扩散和图像分割。
机译:稀疏编码模型展示了一些非经典的接收场效应
机译:稀疏编码模型展示了一些非经典的接收场效应