1 citations · 2 across the 3 of their papers we have counts for
4 papers
Sparsifying and Down-scaling Networks to Increase Robustness to Distortions
Sergey Tarasenko
It has been shown that perfectly trained networks exhibit drastic reduction in performance when presented with distorted images. Streaming Network (STNet) is a novel architecture c…
Streaming Networks: Increase Noise Robustness and Filter Diversity via Hard-wired and Input-induced Sparsity
Sergey Tarasenko, Fumihiko Takahashi
The CNNs have achieved a state-of-the-art performance in many applications. Recent studies illustrate that CNN's recognition accuracy drops drastically if images are noise corrupte…
Applications of the Streaming Networks
Sergey Tarasenko, Fumihiko Takahashi
Most recently Streaming Networks (STnets) have been introduced as a mechanism of robust noise-corrupted images classification. STnets is a family of convolutional neural networks,…
Streaming Networks: Enable A Robust Classification of Noise-Corrupted Images
Sergey Tarasenko, Fumihiko Takahashi
The convolution neural nets (conv nets) have achieved a state-of-the-art performance in many applications of image and video processing. The most recent studies illustrate that the…