21 citations · 37 across the 7 of their papers we have counts for
4 papers · 1 filter
YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems
Ivan Lazarevich, Matteo Grimaldi, Ravish Kumar +3
We present YOLOBench, a benchmark comprised of 550+ YOLO-based object detection models on 4 different datasets and 4 different embedded hardware platforms (x86 CPU, ARM CPU, Nvidia…
QReg: On Regularization Effects of Quantization
MohammadHossein AskariHemmat, Reyhane Askari Hemmat, Alex Hoffman +6
In this paper we study the effects of quantization in DNN training. We hypothesize that weight quantization is a form of regularization and the amount of regularization is correlat…
Post-training deep neural network pruning via layer-wise calibration
Ivan Lazarevich, Alexander Kozlov, Nikita Malinin
We present a post-training weight pruning method for deep neural networks that achieves accuracy levels tolerable for the production setting and that is sufficiently fast to be run…
Neural Network Compression Framework for fast model inference
Alexander Kozlov, Ivan Lazarevich, Vasily Shamporov +2
In this work we present a new framework for neural networks compression with fine-tuning, which we called Neural Network Compression Framework (NNCF). It leverages recent advances…