Significant progress has been made in boundary detection with the help of convolutional
neural networks. Recent boundary detection models not only focus on real object boundary …

Neurophysiological evidence demonstrates that classical receptive field responses in the
primary visual cortex can be modulated by the non-classical receptive field. Although …

There has been significant progress in contour detection with the development of
convolutional neural networks. To improve the detection performance of the object contour …

Physiological studies have revealed that the center–surround mechanism widely exists in
the primary stages of the human visual system, such as the retina, lateral geniculate nucleus …

As the basis of high-level visual tasks, edge detection is significant. Most of the encoder-
decoder edge detection methods used convolutional neural networks, such as VGG16 or …

In this era of artificial intelligence, deep neural networks like Convolutional Neural Networks
(CNNs) have emerged as front-runners, often surpassing human capabilities. These deep …

It is challenging to observe the polarization information of ships in sea fog weather due to
the depolarization phenomenon. Depolarization refers to the phenomenon that the …

The review delves into creating an understandable framework for machine learning in
robotics. It stresses the significance of machine learning in materials science and robotics …

Considering the subjectivity of the contour detection task and the characteristics of the visual
nerve, the traditional contour detection models simulate the surrounding suppression effect …

基于视通路结构分级响应与动态传递的方式, 本文提出了一种图像轮廓检测的新方法.
针对视网膜感光细胞的暗视觉特性, 建立亮度自适应的暗视野调节模型, 利用多尺度经典感受野 …