Deep Learning Based Object Detection (Fast R-CNN) in the Microsoft Cognitive Toolkit

  • R1
  • 第 2 天,17:25‑18:10
  • 中文演講/英文投影片
  • 資料分析
  • 中階

This session showcases work on generic object detection using deep learning. We use the state-of-the-art object detector in the Microsoft Cognitive Toolkit (CNTK) called Fast R-CNN based on Python. Fast R-CNN is based on a Deep Neural Network which was pre-trained on millions of images.

演講詳細內容

The objective of the talk is to describe the DNN technology and show the full object detection pipeline encompassing image annotation, model training, evaluation. Fast R-CNN is a fast framework for object detection with deep ConvNets.Fast R-CNN was initially described in an [arXiv tech report](http://arxiv.org/abs/1504.08083) and later published at ICCV 2015. Microsoft Cognitive Toolkit (CNTK), an MIT Licensed open source deep-learning toolkitthat describes neural networks as a series of computational steps via a directed graph. It supports both Linux and Windows. Based on researchers at HKBU, CNTK’s LSTM performance is 5-10x faster than the other toolkits. The session introduct how to combine the state of art algoritm and toolkit to do image Object Detection.

投影片連結

講者介紹

Herman Wu

Been a Java Developers for 3 years.
Work at Microsoft as a sr. software engineer.