GitHub

Real-Time Object Detection Meets DINOv3

DEIMv2 is an evolution of the DEIM framework while leveraging the rich features from DINOv3. Our method is designed with various model sizes, from an ultra-light version up to S, M, L, and X, to be ...
GitHub

Rethinking Multi-modal Object Detection from the Perspective of Mono-Modality Feature Learning

This repository is the official Pytorch implementation for the paper Rethinking Multi-modal Object Detection from the Perspective of Mono-Modality Feature Learning. If you have any questions, please ...
IEEE

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI

Abstract: Autism Spectrum Disorder (ASD) is a genetic and neurological condition that leads to difficulties in communication and social interaction. The global concern associated with ASD diagnosis is ...

Tenstorrent QuietBox tested: A high-performance RISC-V AI workstation trapped in a software blackhole

The $12K machine promises AI performance can scale to 32 chip servers and beyond but an immature software stack makes ...
IEEE

Intrusion Detection in IoT and IIoT: Comparing Lightweight Machine Learning Techniques Using TON_IoT, WUSTL-IIOT-2021, and EdgeIIoTset Datasets

Abstract: The security of Internet of Things (IoT) and Industrial Internet of Things (IIoT) systems has been significantly enhanced through the integration of effective intrusion detection systems ...
Ars Technica

I’ve already been using a “Steam Machine” for months, and I think it’s great

Valve’s second big foray into first-party PC hardware isn’t a sequel to the much-imitated Steam Deck portable, but rather a desktop computer called the Steam Machine. And while it could go on your ...
The Conversation

How do ‘AI detection’ tools actually work? And are they effective?

T.J. Thomson receives funding from the Australian Research Council. He is an affiliate with the ARC Centre of Excellence for Automated Decision Making & Society. Aaron J. Snoswell receives research ...