Category: Computer Vision

In this part of the Deep Learning with Keras series, we will learn some of the most useful concepts. We will cover topics like Callbacks in Keras, saving models and restoring models. You will also learn about Tensorboard visualization which is an important part of Keras callbacks and analyzing and training models. This is the […] ...

Preparing data for deep learning is one of the most important steps. Deep neural networks need a lot of data most of the time. Perhaps, this is one of the drawbacks when using deep learning to solve a problem. There are many solutions out there to tackle this situation. But what if we do not […] ...

Updated on 21 April, 2020. LeNet – 5 is a great way to start learning practical approaches of Convolutional Neural Networks and computer vision. The LeNet – 5 architecture was introduced by Yann LeCun, Leon Bottou, Yoshua Bengio and Patrick Haffner in 1998. This architecture quickly became popular for recognizing handwritten digits and document recognition. […] ...

Computer Vision and Deep Learning together have given some novel solutions to many of the real world problems. And automatic traffic sign recognition is one of them. Recognizing traffic signs is one of the most important aspects when considering road safety and automated driving. Manual detection, classification, and hard coding are not possible when visualizing […] ...

Convolutional Neural Networks (CNN) have a come a long way in recent years. CNNs have been really beneficial for the field of deep learning for computer vision and image processing. In this article, we will be analyzing the common architectures of CNN. We will also be discussing the variants of CNN that have provided the […] ...