Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments

10 November 2023

Papers citing "Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments"

5 / 5 papers shown

Title
Overcoming Oscillations in Quantization-Aware Training Markus Nagel Marios Fournarakis Yelysei Bondarenko Tijmen Blankevoort MQ 111 101 0 21 Mar 2022
TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation R. Liu Kailun Yang Alina Roitberg Jiaming Zhang Kunyu Peng Huayao Liu Yaonan Wang Rainer Stiefelhagen ViT 47 36 0 27 Feb 2022
FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference D. Khudia Jianyu Huang Protonu Basu Summer Deng Haixin Liu Jongsoo Park M. Smelyanskiy FedML MQ 51 46 0 13 Jan 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,027 0 06 Mar 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,572 0 17 Apr 2017