Object Detection

When you train yolo nas on custom dataset, you’re taking an object detection model that was designed as a strong, general-purpose detector and adapting it to your specific problem. Instead of relying only on COCO-style everyday scenes, you can teach YOLO-NAS to recognize underwater creatures like fish, jellyfish, sharks, or penguins in noisy, low-contrast aquarium […]

YOLO NAS object detection is all about combining modern deep learning with real-world practicality. At its core, YOLO NAS is a family of object detection models designed to spot and locate multiple objects in an image or video frame in real time. Instead of scanning an image piece by piece, the model “looks” at the

YOLOv8 small object detection sits at the intersection of two big needs in modern computer vision: real-time performance and the ability to reliably detect tiny targets in busy, high-resolution scenes. While classic detectors can easily find large, clear objects, they often struggle when cars become just a few pixels wide in a traffic camera, or

Modern hospitals see thousands of fracture cases every year, and most of them are confirmed or ruled out using X-ray images. Interpreting those X-rays quickly and accurately is critical, but it’s also repetitive, tiring work for radiologists and orthopedic teams. That’s exactly where yolov8 bone fracture detection comes in: it combines state-of-the-art object detection with

Object detection becomes truly powerful when the model understands your world instead of just COCO-style benchmarks. That’s where yolov8 custom object detection comes in. Instead of detecting generic categories like dogs or cars, you fine-tune YOLOv8 on your own dataset, with your own labels, and tailor the model to a specific domain such as ships

When you train YOLOv8 on custom dataset, you turn a general-purpose object detector into a specialist that understands exactly the objects you care about.Instead of relying on COCO’s people, cars, and dogs, you can teach YOLOv8 to recognise things like playing cards, medical instruments, or products on a shelf with high speed and accuracy. The

Bringing object detection from YouTube video into focus Object detection from youtube video is all about teaching your code to “see” what is happening inside an online video stream.Instead of manually downloading a file and running offline analysis, you connect directly to a YouTube URL, grab each frame in real time, and let a deep

Getting started with YOLOv8 dental object detection In modern dentistry, X-rays are no longer just static images on a screen. With yolov8 dental object detection, those images can be transformed into structured data that highlights teeth, restorations, lesions, and other findings automatically. Instead of manually scanning every millimeter of a radiograph, a trained YOLOv8 model

Understanding EigenCAM in Deep Learning EigenCAM is a visualization technique that helps you see where a neural network is focusing when it makes a decision. Instead of treating a deep model as a black box, EigenCAM uses the internal activations of a convolutional neural network (CNN) to create a heatmap that highlights the most influential

Getting Ready to Train YOLOv5 on a Custom Dataset Training YOLOv5 on a custom dataset is one of the most powerful ways to move from “toy examples” to real-world computer vision solutions. Instead of relying only on generic datasets like COCO, you can train yolov5 on a custom dataset that reflects your exact problem: boats