Abstract: Unsupervised anomaly detection (UAD) methods typically detect anomalies by learning and reconstructing the normative distribution. However, since anomalies constantly invade and affect their ...
Artificial intelligence detectors are increasingly used to check the veracity of content online. We ran more than 1,000 tests and found several strengths and plenty of weaknesses. By Stuart A.
This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...
Scary Shawarma Kiosk: The Anomaly is a Roblox experience where you run a humble shawarma shop. Rather than simply serving customers and making shawarma, however, your main focus here is your customers ...
Hybrid Dual-Heterogeneous Knowledge Distillation Network for Anomaly Detection in Retinal OCT Images
Abstract: Unsupervised medical anomaly detection aims to identify abnormal images by training exclusively on normal samples, thereby enabling the detection of disease related irregularities without ...
We have attempted to develop a Fracture Line Detection System using MATLAB and its Image Processing Toolbox. The system aims to assist radiologists by processing X-ray images to automatically ...
Ailsa Ostovitz has been accused of using AI on three assignments in two different classes this school year. "It's mentally exhausting because it's like I know this is my work," says Ostovitz, 17. "I ...
I published a post last year showcasing six pairs of images, challenging readers to try and figure out which ones were made with AI. Out of the six image pairs, I was surprised to learn that more than ...
WASHINGTON (7News) — Now it’s time for a little game: Is it real or fake? 7News anchor Adrianna Hopkins has been digging into the rapidly evolving world of artificial intelligence -- and you’ve likely ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results