The success of current deep saliency models heavily depends on large amounts of annotated human fixation data to fit the highly non-linear mapping between the stimuli and …
In recent years, salient object detection (SOD) has achieved significant progress with the help of convolution neural network (CNN). Most of the state-of-the-art methods segment the …
Techniques for detecting salient objects mimic human behavior by recognizing the most noticeable parts of images as objects. Salient object detection has attracted many …
P Hao, M Yang, N Zheng - Multimedia Tools and Applications, 2022 - Springer
Most existing low-light image enhancement methods enhance whole low-light image indiscriminately with the neglect of its subjective content, which may lead to over …
VK Singh, N Kumar - Multimedia Tools and Applications, 2022 - Springer
Salient object detection is a challenging research area, which aims to highlight significant region of the visual scene more accurately and quickly. In this research direction, we …
D Berga, X Otazu - Neural Computation, 2022 - direct.mit.edu
Lateral connections in the primary visual cortex (V1) have long been hypothesized to be responsible for several visual processing mechanisms such as brightness induction …
CA Parraga - Encyclopedia of Computational Neuroscience, 2022 - Springer
Introduction Studies of categorical decision-making attempt to understand behavior by probing how different features of complex and changing environments guide the selection of …
J Wang, J Liu, Y Zhang, H Zhu, Y Han, Y Zhang… - Proceedings of Sixth …, 2022 - Springer
Due to the limited number of implantable microelectrodes, subjects worn by retinal prosthesis received only limited discrete light spot (called artificial vision). Thus, the external …