eLife

New idtracker.ai rethinks multi-animal tracking as a representation learning problem to increase accuracy and reduce tracking time

Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.
IEEE

A comprehensive study on the performance of different Multi-class Classification Algorithms and Hyperparameter Tuning Techniques using Optuna

Abstract: Multi-class classification talks about classification tasks that have three or more classes. It takes the assumption that every data sample in the dataset is assigned to one and only one ...
TMCnet

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

SHENZHEN, China, Oct. 24, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network ...
IEEE

Multiclass IFROWNN Classification Algorithm Using OVA and OVO Strategy

Abstract: All basic algorithms are commonly used for decision making, in the field of machine learning. But basic algorithms are used to handle more often balanced data. Now a day, enormous people ...
Game Rant

Dungeons and Dragons: The Pros and Cons of Multiclassing Explained

Shayna Josi is a Features Writer from South Africa. Shayna has always been passionate about stories, and has dedicated her life to learning how to tell them. Aside from writing about her favorite ...