Abstract: In remote sensing classification problems, high visual similarity between scenes reduces the classification performance of traditional methods. Therefore, advanced deep neural network models ...

Abstract: Deep learning has emerged as a critical paradigm in hyperspectral image (HSI) classification, addressing the inherent challenges posed by high-dimensional data and limited labeled samples.

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...

A production-ready deep learning project for time-series image classification using EfficientNet/NFNet with PyTorch Lightning. This project implements transfer learning for multi-class classification ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

90% accuracy resnet-like CNN from scratch for Intel Image Classification dataset WITHOUT transfer learning and with complex metrics.

GRANTS PASS, Ore — Wildlife Images executive director Dave Siddon is no stranger to the Sunrise studio, and he always brings a friend or two along with him when he visits. This morning was no ...