Neural networks based on in-sensor computing of optoelectronic memristor
Z Zhang, Q Wang, G Shi, Y Ma, J Zeng, G Liu - Microelectronic Engineering, 2024 - Elsevier
The separation band of perception, storage, and computation modules in vision systems
based on traditional von Neumann architectures leads to latency and power consumption …
based on traditional von Neumann architectures leads to latency and power consumption …
Unraveling the complexity of rat object vision requires a full convolutional network-and beyond
Despite their prominence as model systems to dissect visual cortical circuitry, it remains
unclear whether rodents are capable of truly advanced processing of visual information …
unclear whether rodents are capable of truly advanced processing of visual information …
Shape-Biased Learning by Thinking Inside the Box
Deep Neural Networks (DNNs) may surpass human-level performance on vision tasks such
as object recognition and detection, but their model behavior still differs from human …
as object recognition and detection, but their model behavior still differs from human …
Gradient-Based Convolutional Neural Network Feature Visualization
L He - 2024 - adwenpub.com
This paper proposes a novel method for evaluating the robustness of visualization. In terms
of effectiveness, the paper assesses visual coherence, visual resolution, and multi-target …
of effectiveness, the paper assesses visual coherence, visual resolution, and multi-target …
[HTML][HTML] Convolutional neural network models applied to neuronal responses in macaque V1 reveal limited nonlinear processing
HY Miao, F Tong - Journal of Vision, 2024 - tvst.arvojournals.org
Computational models of the primary visual cortex (V1) have suggested that V1 neurons
behave like Gabor filters followed by simple nonlinearities. However, recent work employing …
behave like Gabor filters followed by simple nonlinearities. However, recent work employing …