The machine-learning programs that underpin their ability to “see” still have blind spots—but not for much longer ...
This project leverages state-of-the-art deep learning models to classify potato leaf diseases with high accuracy. Early detection helps farmers prevent crop loss and increase yield. Multi-class image ...
A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...
Abstract: This study assesses the performance of CustomNet, a lightweight neural network model trained using NumPy and Pandas, compared to the VGG-16 architecture on the datasets of MNIST, Fashion ...
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, ...
A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
This repository contains an end-to-end implementation of a convolutional neural network (CNN) trained on the CIFAR-10 dataset for multi-class image classification. It demonstrates fundamental deep ...
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 ...
Laboratory of Micro-Optoelectronics and Nanostructures (LR99/E929), Faculty of Sciences of Monastir, University of Monastir, Monastir, Tunisia Alzheimer’s disease (AD) is a progressive ...
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