Deep Learning
Zero to Hero: A Quick Guide to Object Tracking: MDNET, GOTURN, ROLO
In today’s article, we shall deep dive into video object tracking. Starting from the basics, we shall understand the need for object tracking, and then go through the challenges and algorithmic models to understand visual object tracking, finally, we shall cover the most popular deep learning based approaches to object tracking including MDNET, GOTURN, […]
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Neural Architecture Search
Neural network architecture design is one of the key hyperparameters in solving problems using deep learning and computer vision. Various neural networks are compared on two key factors i.e. accuracy and computational requirement. In general, as we aim to design more accurate neural networks, the computational requirement increases. In this post, we shall learn about […]
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Running Deep Learning models in OpenCV
The largest computer vision library OpenCV can now deploy Deep learning models from various frameworks such as Tensorflow, Caffe, Darknet, Torch. This tutorial is a step by step guide with code how I deployed YOLO-V2 model in OpenCV. OpenCV: The open source computer vision library for everyone: OpenCV has been the go-to library for computer […]
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Choosing a Deep Learning Framework: Tensorflow or Pytorch?
One of my friends is the founder and Chief data scientist at a very successful deep learning startup. 2017 was a good year for his startup with funding and increasing adoption. However, on a Thursday evening last year, my friend was very frustrated and disappointed. The framework on which they had built everything in last […]
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Object Detection using Single Shot Multibox Detector
In a previous post, we covered various methods of object detection using deep learning. In this blog, I will cover Single Shot Multibox Detector in more details. SSD is one of the most popular object detection algorithms due to its ease of implementation and good accuracy vs computation required ratio. Work proposed by Christian Szegedy […]
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