Advancing object detection technology, YOLOv9 stands out as a significant development in Object Detection, created by Chien-Yao Wang and his team. This new version introduces innovative methods such ...
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Fine-Tuning LLMs using PEFT
Large Language Models (LLMs) have taken the world by storm, demonstrating an uncanny ability to understand and generate human language. However, while they excel at grasping general language patterns, ...
Depth Anything: Accelerating Monocular Depth Perception
Depth Anything represents a groundbreaking advancement in the field of monocular depth perception. This research article outlines the innovative approach taken in designing the Depth Anything model, ...
Deciphering LLMs: From Transformers to Quantization
This article is the first part of the Mastering LLMs series, Here we will discuss what LLMs are, their use cases, and the tasks they perform. We will also explain the underlying Transformer ...
YOLO Loss Function Part 2: GFL and VFL Loss
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 ...
YOLOv8 Object Tracking and Counting with OpenCV
In the realm of computer vision, YOLOv8 object tracking is revolutionizing the way we approach real-time tracking and analysis of moving objects. This article takes a close look at the fascinating ...
