Abstract: This study examines the effectiveness of using machine learning-based image recognition model for classifying common diseases in crops. This study addresses the critical need for swift and ...

The First Hospital of Hunan University of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China Background: Breast cancer remains the most prevalent malignancy in women globally, ...

Features Loads pre-trained neural network parameters from CSV files Processes the MNIST dataset (60,000 images) Interactive visualization of MNIST images with SDL2 Forward pass implementation for ...

Methods: This study prospectively evaluated 357 participants (101 with sarcopenia and 256 without sarcopenia) for training, encompassing three types of data: muscle ultrasound images, clinical ...

This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset. It closely follows the tutorial by The Clever ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

Abstract: The recognition of handwritten digits has been among the most enduring fundamental problems explored in the field of machine learning and computer vision. The objective of this work is to ...