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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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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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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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