IEEE

Approximate Softmax Functions for Energy-Efficient Deep Neural Networks

Abstract: Approximate computing has emerged as a new paradigm that provides power-efficient and high-performance arithmetic designs by relaxing the stringent requirement of accuracy. Nonlinear ...
GitHub

Dual Selective Fusion Transformer Network for Hyperspectral Image Classification

DSFormer is a novel Dual Selective Fusion Transformer Network for HSI classification. It adaptively selects and fuses features from diverse receptive fields to achieve joint spatial-spectral context ...
GitHub

vision-transformer-image-classification

Explore fine-tuning the Vision Transformer (ViT) model for object recognition in robotics using PyTorch. This tutorial covers setup, training, and evaluation processes, achieving impressive accuracy ...
IEEE

Real-Time Gumbel-Softmax Adaptive Thresholding for Robust Object Classification Under High Illumination Conditions

Abstract: This paper proposes a novel object classification system integrating a dual-imaging CMOS Image Sensor (CIS) with a real-time Gumbel-Softmax-based threshold selection module to address ...