A survey on approximate edge AI for energy efficient autonomous driving services
Autonomous driving services depends on active sensing from modules such as camera,
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …
Comprehensive comparisons of uniform quantization in deep image compression
In deep image compression, uniform quantization is applied to latent representations
obtained by using an auto-encoder architecture for reducing bits and entropy coding …
obtained by using an auto-encoder architecture for reducing bits and entropy coding …
Mixed entropy model enhanced residual attention network for remote sensing image compression
J Gao, Q Teng, X He, Z Chen, C Ren - Neural Processing Letters, 2023 - Springer
In recent years, deep learning has been widely employed in the field of image compression,
the most significant of which is the lossy image compression method on the basis of …
the most significant of which is the lossy image compression method on the basis of …
Deep feature extraction and compression for human–machine vision
Latent representation features in deep learning (DL) exhibit excellent potential for visual
data applications. For example, in traffic monitoring and video surveillance, the features …
data applications. For example, in traffic monitoring and video surveillance, the features …
Using Asymmetric Attention Mechanism Access Class Barring with Gated Recurrent Unit for an End-to-end Image Compression
MJC Samonte, S Liu, Y Li - 2023 IEEE 15th International …, 2023 - ieeexplore.ieee.org
The exponential expansion of the Internet has resulted in an overwhelming abundance of
multimedia data. However, image and video compression technology faces challenges such …
multimedia data. However, image and video compression technology faces challenges such …