IEEE

Stacking Binary Neural Networks for Efficient Edge-Based Waste Classification

Abstract: Waste classification poses significant challenges owing to rapid societal development and increasing waste generation. Although deep neural networks have demonstrated remarkable results in ...
IEEE

Optimizing Neural Network Architecture for Binary Classification Using Evolutionary Algorithms

Abstract: Neural network performance heavily depends on the architecture chosen for specific tasks, such as binary classification. Rather than relying on conventional ...
GitHub

Pull requests: Arty3/Binary-Image-Classification-Neural-Network

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.
C&EN

Leveraging Deep Learning to Address Diagnostic Challenges with Insufficient Image Data

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 ...
Scientific Research Publishing

Zhang, X., Zhao, J.B. and LeCun, Y. (2015) Character-Level Convolutional Networks for Text Classification.

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
Phys.org

Researchers develop neural network for large-scale celestial object classification

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 ...
GitHub

Cesarui/Nasa-ExoPlanet-ML-Model

This project implements a binary classification neural network to identify confirmed exoplanets from NASA's Kepler mission data. The model analyzes five key planetary features and predicts whether a ...