Image segmentation is one of the most fundamental tasks in Computer Vision. With their Segment Anything Model (SAM), last year, Meta AI put forth the world's first foundation model for image ...
Enhancing Image Segmentation using U2-Net: An Approach to Efficient Background Removal
U2-Net (popularly known as U2-Net) is a simple yet powerful deep-learning-based semantic segmentation model that revolutionizes background removal in image segmentation. Its effective and ...
YOLOv9 Instance Segmentation on Medical Dataset
Deep learning has revolutionized medical image analysis. By identifying complex patterns within medical images, it helps us to interpret crucial insights about our biological systems. So, if you ever ...
SegFormer 🤗 : Fine-Tuning for Improved Lane Detection in Autonomous Vehicles
SegFormer: Segmentation has heavily impacted the development of advanced driver assistance systems. It has been pivotal in the rapid development of autonomous vehicle technology. It is built up of ...
Semantic Segmentation using KerasCV DeepLabv3+
The KerasCV series continues with this second article. Continuing from the previous post, where we discussed Object Detection using KerasCV YOLOv8, this article discusses solving a semantic ...
PaddlePaddle: Exploring Object Detection, Segmentation, and Keypoints
PaddlePaddle: Welcome to our guide of machine learning frameworks, where we'll examine PaddlePaddle, TensorFlow, and PyTorch. Recent benchmark tests have revealed PaddlePaddle as a potential ...
