Imagine you’re watching a travel vlog on YouTube, and you turn on the image captions feature. As the video shows a stunning view of Mount Fuji, a caption appears: “Snow-capped Mount Fuji at sunrise ...
In the groundbreaking paper “Attention is all you need”, Transformers architecture was introduced for sequence to sequence tasks in NLP. Models like Bert, GPT were built on the top of Transformers ...
Sapiens, a family of foundational Human Vision Models by Rawal et al., from Meta, achieves state-of-the-art results for human centric tasks like 2D pose estimation, body-part segmentation, depth ...
Detecting small objects in aerial imagery, particularly for critical applications like sea rescue, presents unique challenges. Timely detection of people in the water can mean the difference between ...
In the preceding article, YOLO Loss Functions Part 1, we focused exclusively on SIoU and Focal Loss as the primary loss functions used in the YOLO series of models. In this article, we will dive ...
The YOLO (You Only Look Once) series of models, renowned for its real-time object detection capabilities, owes much of its effectiveness to its specialized loss functions. In this article, we delve ...
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