Devdiscourse

Why AI systems struggle with identities that resist fixed labels

A new academic study argues that the structural reliance of artificial intelligence (AI) systems on classification models ...

MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...
Frontiers

Traditional machine learning in biomedical image analysis: before you go too deep

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
Rome Sentinel

SRC gets AFRL contract for next-gen AI, machine learning

ROME — SRC, a not-for-profit defense research and development company headquartered in Syracuse with an office in Rome on the Griffiss Business and Technology Park, has been awarded a $24M contract by ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Hacker

I-Machine Learning for the Birds: Ukwakha I-Our Own Bird Vocalization Classifier

I-Machine Learning for the Birds: Ukwakha I-Our Own Bird Vocalization Classifier nge Picture in the Noise 20 imiz read 2025/06/08 XH ...
IEEE

ES-GP: An Ensemble Surrogate-Assisted Genetic Programming Approach to Image Classification

Abstract: Genetic Programming (GP) is a promising evolutionary machine learning technique for image classification, known for its ability to evolve flexible, effective, and interpretable models.
IEEE

Hybrid Makes Better: Hybrid Differential Privacy Medical Image Classification Based on Federated Learning

Abstract: Machine learning has the potential to revolutionize medical image classification. However, machine learning requires large medical datasets to improve accuracy, which will compromise patient ...