Abstract: In recent years, object detection utilizing both visible (RGB) and thermal infrared (IR) imagery has garnered extensive attention and has been widely implemented across a diverse array of ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Abstract: The loss function and feature extraction framework are essential parts of the algorithm design and significantly affect the accuracy of oriented object detection in remote sensing images.

Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and Fundamental Forces from Imperial College London. Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and ...

Researchers have successfully trained a new AI foundation model capable of predicting medical conditions using Apple Watch data, achieving high accuracy even when that data is incomplete or irregular.

While Yann LeCun was still Meta’s Chief AI Scientist, he proposed the Joint-Embedding Predictive Architecture, or JEPA, which essentially teaches an AI to infer the meaning of missing data rather than ...

Experts are sounding the alarm over YouTube’s deepfake detection tool — a new safety feature that could allow Google to train its own AI bots with creators’ faces, according to a report. The tool ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

Can you only finetune object detection at the pretrained size? I've only used the dinov3 eomt semantic segmentation in lightly-train before and was able to use any size If I try setting image size to ...

Add Yahoo as a preferred source to see more of our stories on Google. The black ring and central dot show infrared image of a distant galaxy distorted by a gravitation lens. (CREDIT: Devon Powell, Max ...