For a detailed project overview, architecture diagrams, code explanations, and next steps, please refer to the full write‑up (PDF): ├─ ETL/ # Data extraction & mask generation utilities ├─ dataset.py ...
Introduction: Weeds are a major factor affecting crop yield and quality. Accurate identification and localization of crops and weeds are essential for achieving automated weed management in precision ...
U-Net and its variants have been widely used in the field of image segmentation. In this paper, a lightweight multi-scale Ghost U-Net (MSGU-Net) network architecture is proposed. This can efficiently ...
Targeted marketing and personalization have evolved dramatically in the last decade. Engaging an audience overwhelmed by the internet’s content farm requires meeting fans where they are, speaking ...
This is an experimental Tiled Image Segmentation project for Oral-Cancer based on the Tensorflow-Image-Segmentation-API, and Oral-Cancer-ImageMask-Dataset-V1.zip As shown in ...
Medical image segmentation, crucial for diagnosis and treatment, often relies on UNet’s symmetrical architecture to delineate organs and lesions accurately. However, UNet’s convolutional nature needs ...
Abstract: It is still a challenging task to perform the semantic segmentation with high accuracy due to the complexity of real picture scenes. Many semantic segmentation methods based on traditional ...
Diffusion models represent a cutting-edge approach to image generation, offering a dynamic framework for capturing temporal changes in data. The UNet encoder within diffusion models has recently been ...
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