Critics of the overuse of technology in schools argue that it has led to students losing the ability to concentrate and ...

Abstract: Deep learning-based approaches have achieved remarkable success in various image-based dietary assessment applications, including food detection and estimating portion sizes. However, most ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

ABSTRACT: Morphological segmentation is foundational for Natural Language Processing in morphologically rich languages, such as Amharic, yet progress is constrained by limited gold annotations and ...

Learn the concept of in-context learning and why it’s a breakthrough for large language models. Clear and beginner-friendly explanation. #InContextLearning #DeepLearning #LLMs This is what happens ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

What happens when multiple AI agents work together to solve complex problems? In this video, we dive into multi-agent systems in deep learning—how they work, why they matter, and how tools like ...