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We've put up the largest collection of machine learning models in Core ML format, to help iOS, macOS, tvOS, and watchOS developers experiment with machine learning techniques. We've created a site with better visualization of the models CoreML.Store, and are working on more advance features. If you've converted a Core ML model, feel free to submit an issue.
Please refer to PyTorch implementation for an up-to-date implementation. FuseNet is developed as a general architecture for deep convolutional neural network (CNN) to train dataset with RGB-D images. It can be used for semantic segmentation, scene classification and other applications. This repository is an official release of this paper, and it is implemented based on the BVLC/caffe framework.
This projects implements the yolov2 (https://pjreddie.com/darknet/yolov2/) RegionLayer in Go. It is heavily inspired by duangenquan's C++-RegionLayer implementation (https://github.com/duangenquan/YoloV2NCS). This projects makes use of gocv (https://gocv.io) and go-ncs (https://github.com/hybridgroup/go-ncs/), both from hybridgroup (https://github.com/hybridgroup).