In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A ...

The object detection required for machine vision applications such as autonomous driving, smart manufacturing, and surveillance applications depends on AI modeling. The goal now is to improve the ...

Q-FlexiViT is evaluated on standard intrusion-detection datasets containing multiple attack types and normal traffic. Using ...

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. (In partnership with Paperspace) In recent years, the transformer model has ...

Accurately estimating fruit size directly on plants is essential for precision agriculture, enabling data-driven crop management and improving yield prediction. Traditional fruit detection and ...