Abstract: Remote sensing image semantic segmentation has extensive applications in land resource planning and smart cities. Due to the problems of unclear boundary segmentation and insufficient ...
Introduction: Weeds compete with crops for water, nutrients, and light, negatively impacting maize yield and quality. To enhance weed identification accuracy and meet the requirements of precision ...
While I found the config files and code for training and distilling DinoV3, as well as training the classification head and doing the text alignment, I didn't find training code for semantic ...
Modern software engineering faces growing challenges in accurately retrieving and understanding code across diverse programming languages and large-scale codebases. Existing embedding models often ...
Abstract: 4D LiDAR semantic segmentation classifies the semantic category of each LiDAR point and detects whether it is dynamic, a critical ability for tasks like obstacle avoidance and autonomous ...
Python libraries are pre-written collections of code designed to simplify programming by providing ready-made functions for specific tasks. They eliminate the need to write repetitive code and cover ...
Overall Performance Metrics: Side-by-side comparison of Mean IoU, Dice Score, and Pixel Accuracy. Per-Class Performance Analysis: A detailed, sorted breakdown of IoU scores for each semantic class, ...
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