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Enhanced Sharp-GAN For Histopathology Image Synthesis
To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization.
Sharp-GAN: Sharpness Loss Regularized GAN for Histopathology Image Synthesis
Conditional generative adversarial networks have been applied to generate synthetic histopathology images to alleviate this issue, but current approaches fail to generate clear contours for overlapped and touching nuclei.
Potato Crop Stress Identification in Aerial Images using Deep Learning-based Object Detection
Recent research on the application of remote sensing and deep learning-based analysis in precision agriculture demonstrated a potential for improved crop management and reduced environmental impacts of agricultural production.
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