IEEE

SFTNet: Spatial-Frequency Transformer Network for Learned Image Compression

Abstract: In learned image compression (LIC), most existing methods process spatial domain information through convolutional neural networks (CNNs) or Transformers. However, they struggle to model ...
Scientific Research Publishing

A Spatio-Temporal Prediction Model for Wall Turbulence Based on Hybrid Neural Networks ()

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...

Nvidia shrinks LLM memory 20x without changing model weights

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.
IEEE

Performance Evaluation of Support Vector Machine and Stacked Autoencoder for Hyperspectral Image Analysis

Abstract: In the world of remote sensing, hyperspectral imaging has emerged as a powerful tool that captures incredibly detailed information about our environment. These images contain hundreds of ...