Aug 24, 2022 · Our approach is remarkably lightweight, both during training and inference, highly effective and achieves excellent rate-distortion performance.

Our approach is remarkably lightweight, both during training and inference, highly effective and achieves excellent rate-distortion performance.

Aug 24, 2022 · METHOD. In this section, we describe a systematic approach to the design and training of low-complexity bottleneck layers for flexible workload ...

A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing. Parual Datta, Nilesh Ahuja, V. Srinivasa ...

A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing · Parual Datta, Nilesh Ahuja, V Srinivasa ...

Optimizing the pipeline for both compression ... A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing.

Apr 25, 2024 · A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing. ICPR 2022: 182-188. [i2]. view.

A low-complexity approach to rate-distortion optimized variable bit-rate compression for split dnn computing. P Datta, N Ahuja, VS Somayazulu, O Tickoo. 2022 ...

In this work, we present a method to train split-DNN models for distributed, rate-distrotion optimized visual-analytics.

A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing · no code implementations • 24 Aug 2022 • Parual ...