In this paper, we propose a Partial Gated Feedback Recurrent Neural Network (PGF-RNN) for the identification of lossless compression algorithms. We modify the gated recurrent units to improve the ...

With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different types of hardware ...

Compression is a process of reducing the size of data by removing redundancy, encoding patterns, or applying algorithms. Compression can be applied to different types of data, such as text, images ...

Features Multi-Compression Techniques: Utilizes multiple compression algorithms (e.g., Deflate, Gzip) for optimal data reduction. Lossless Compression: Ensures no data loss during the compression and ...

Implementation of "Domain-adaptive deep network compression", ICCV 2017 - mmasana/DALR. Skip to content. Navigation Menu Toggle navigation. ... PhD student at LAMP research group at Computer Vision ...

Data compression is essential to large-scale data centers to save both storage and network bandwidth. Current software based method suffers from high computational cost with limited performance. In ...

“Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing,” ...

The graph below shows the total number of publications each year in Video Compression Algorithms and Memory Efficiency. References [1] Accelerating BPC-PaCo through Visually Lossless Techniques .