In semantic segmentation, understanding how a deep learning model arrives at its decisions is crucial—especially in fields like medical imaging, agriculture, and autonomous systems. While U-Net and other architectures can deliver high accuracy, they often act as black boxes. In this blog post, we go beyond prediction accuracy. We’ll visualize Continue Reading
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Multiclass Segmentation in PyTorch using U-Net
Semantic segmentation is a crucial task in computer vision that involves labeling each pixel in an image with its corresponding class. In this blog post, we’ll dive into building a multiclass semantic segmentation pipeline using the U-Net architecture with PyTorch. Our goal is to segment different types of weeds from Continue Reading