169 citations · 361 across the 53 of their papers we have counts for
53 papers
A Proximal Algorithm for Network Slimming
Kevin Bui, Fanghui Xue, Fredrick Park +2
As a popular channel pruning method for convolutional neural networks (CNNs), network slimming (NS) has a three-stage process: (1) it trains a CNN with regularization appl…
Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising
Kevin Bui, Yifei Lou, Fredrick Park +1
Poisson noise commonly occurs in images captured by photon-limited imaging systems such as in astronomy and medicine. As the distribution of Poisson noise depends on the pixel inte…
Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data
Zhijian Li, Biao Yang, Penghang Yin +2
In this paper, we propose a feature affinity (FA) assisted knowledge distillation (KD) method to improve quantization-aware training of deep neural networks (DNN). The FA loss on i…
Difference of Anisotropic and Isotropic TV for Segmentation under Blur and Poisson Noise
Kevin Bui, Yifei Lou, Fredrick Park +1
In this paper, we aim to segment an image degraded by blur and Poisson noise. We adopt a smoothing-and-thresholding (SaT) segmentation framework that finds a piecewise-smooth solut…
Searching Intrinsic Dimensions of Vision Transformers
Fanghui Xue, Biao Yang, Yingyong Qi +1
It has been shown by many researchers that transformers perform as well as convolutional neural networks in many computer vision tasks. Meanwhile, the large computational costs of…
Channel Pruning In Quantization-aware Training: An Adaptive Projection-gradient Descent-shrinkage-splitting Method
Zhijian Li, Jack Xin
We propose an adaptive projection-gradient descent-shrinkage-splitting method (APGDSSM) to integrate penalty based channel pruning into quantization-aware training (QAT). APGDSSM c…