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.


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]( 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.



Herman Wu

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