In this article, we will explore SAM 2, which expands the capabilities of the original SAM to handle both images and videos. It excels in real-time object segmentation, enabling dynamic interaction through prompts and memory attention.
In part 2 of this tutorial series, we look at DETR's Hungarian Algorithm in depth to show how it minimizes cost.
DETR introduces a completely new architecture, setting a new standard in the object detection field. In this article, we explore the Detection Transformer (DETR) concept, highlighting its groundbreaking approach and the significant advancements it brings to object detection technology.
In this article, we explore the architecture of YOLO NAS. We will understand its neural network design, optimization techniques, and highlight the specific improvements it brings over traditional YOLO models.
This article reviews the advancements presented in the paper "Grounding DINO 1.5: Advance the 'Edge' of Open-Set Object Detection." We will explore the methodologies introduced, the impact on open-set object detection, and the potential applications and future directions suggested by this research.
In this article we will explore YOLOv10: The latest in real-time object detection. With improved post-processing and model architecture, YOLOv10 achieves state-of-the-art performance.
Discover YOLO-world through the Paperspace platform. In this piece, we delve deeper into the innovative YOLO-World algorithm to understand its groundbreaking capabilities and implications.
Explore YOLOv9, known for the novel architecture GELAN and Reversible Network Architecture to address the unreliable gradient issue in Deep Neural Network.
In this article, we'll explore how a CNN views and comprehends images without diving into the mathematical intricacies.
