Phil Ferriere's Projects
Phil Ferriere's Artificial Intelligence Nanodegree Projects (reports and code)
A curated list of deep learning resources for computer vision
awesome-semantic-segmentation
Clone of COCO API - Dataset @ http://cocodataset.org/ - with changes to support Windows build and python3
GPU-accelerated Deep Learning on Windows 10 native
A collection of my personal dotfiles
Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.
Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution (CVPR 2017)
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Modern Deep Learning Docker Image
Test/demo web app for R packages like {mscsweblm4r} and {mscstexta4r} that interface with Microsoft Cognitive Services REST APIs.
R Client for the Microsoft Cognitive Services Text Analytics REST API
R Client for the Microsoft Cognitive Services Web Language Model REST API
Fast, accurate and easy to run dense optical flow with python wrapper
Resources of semantic segmantation based on Deep Learning model
Team Three_Explorers 2018 Data Science Bowl Dual U-Net Nuclei Segmentation Solution
Optical Flow Prediction with TensorFlow. Implements "PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume," by Deqing Sun et al. (CVPR 2018)
Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Understanding Convolution for Semantic Segmentation