Tag: Deep Learning Theory

In this post, we discuss the Image Super Resolution Using Deep Convolutional Networks along with the network architectures and experiment results. ...

In this post, we go through the Wide Residual Neural Networks paper. We go through the theory, architecture, experiments, and results of the Wide ResNets. ...

Learn how to implement the VGG11 deep neural network from scratch using the PyTorch deep learning framework. ...

Many of you must have used ResNets for image classification numerous times. And if you are in the field of deep learning for quite some time now, then chances are that you have ResNets as a backbone for object detection as well. But many newcomers in the field of deep learning find it difficult to […] ...

This article explains the different evaluation metrics for deep learning object detection techniques. These include Average Precision (AP), Intersection over Union (IoU), and mean Average Precision (mAP) ...