The pyTorch implementation of two models described in Deep Semantic Text Hashing with Weak Supervision (SIGIR'18)
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Updated
Aug 11, 2022 - Python
The pyTorch implementation of two models described in Deep Semantic Text Hashing with Weak Supervision (SIGIR'18)
Prediction of vegetation coverage maps from High Density Lidar data, in a weakly supervised deep learning setting.
End-to-end CV pipeline that converts raw gameplay footage into labeled YOLO datasets — zero manual annotation. Built with YOLOv8, Tesseract OCR, FFmpeg and Streamlit.
Segmentation of Human Cardiac Subregions - LV, RV, Myocardium. Used Weak Supervision via scribbles.
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