Man’s Search for the most accurate Neural Network Architecture
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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Deep Learning based image Super-Resolution to enhance photos
What if you could use Artificial Intelligence to enhance your photos like those seen on TV? Image super-resolution is the technology which allows you to increase the resolution of your images using deep learning so as to zoom into your images. Check out this hilarious video: What is Image Super-Resolution? Image super-resolution is a software […]
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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 in 2018: 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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Breaking Deep Learning with Adversarial examples using Tensorflow
It’s no news that Deep Learning is super effective and powerful in solving computer vision problems. To keep things in perspective, the top 5 accuracy of NASnet on the ImageNet dataset is 96.2% which is greater than human accuracy on the same task(approx 94.9%). Similarly, deep learning has surpassed or equaled the human level accuracy for […]
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