Universal lesion detection, tagging,and segmentation by MULAN GitHub
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Abstract Multitask Universal Lesion Analysis Network (MULAN) + trained model Environment python, PyTorch Discription MULAN is a CNN for joint detection, tagging, and segmentation of a variety of lesions in CT images. |
Universal lesion classification and retrieval by LesaNet GitHub
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Abstract Lesion Annotation Network (LesaNet) + lesion labels in DeepLesion Environment python, PyTorch Discription LesaNet is a CNN for universal lesion classification and retrieval in diverse CT images. |
Universal lesion detection by 3DCE GitHub
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Abstract 3D Context Enhanced Region-based Convolutional Neural Network (3DCE) Environment python, MXNet Discription 3DCE is an object detection framework which makes use of the 3D context in volumetric image data (and maybe video data) efficiently. |
Self-supervised body part regressor (SSBR) GitHub
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Abstract Self-supervised body part regressor (SSBR) Environment python, caffe Discription Predicts a continuous score for an axial slice in a computed tomography (CT) scan which indicates its relative z position in the body. |
YAN-PRTools Details
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Abstract Yet ANother pattern recognition toolbox Environment Matlab Discription ~40 common pattern recognition algorithms including feature processing, classification, regression, feature selection, and sample selection. |
Domain adaptation toolbox Details
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Abstract A domain adaptation matlab toolbox Environment Matlab Discription Wrappers and implementations of several domain adaptation / transfer learning / semi-supervised learning algorithms. |
FaceRecog GitHub Google code
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Abstract Face Recognition demo in Windows Environment MFC + OpenCV Discription The demo can detect faces from webcam or pictures, then identify it according to the enrolled database. It allows you to train your own classfier using your own pictures, as well as save or load your classifiers or face databases. |
GestureDetect GitHub
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Abstract Gesture detection demo Environment Kinect + Unity3D + C# Discription The demo detects gestures and trains user-defined gesture templates. It uses a template matching algorithm. |