Category: Convolutional Neural Networks

  • Visualizing the Convolutional Filters of the LeNet Model

    First of all, Happy New Year to you all! We have a great year ahead. And, let’s start it with something interesting. We’ve talked about how Convolutional Neural Networks (CNNs) are able to learn complex features from input procedurally through convolutional filters in each layer. But, how does a convolutional filter really look like? In…

  • Using Bottleneck Features for Multi-Class Classification in Keras and TensorFlow

    Training an Image Classification model – even with Deep Learning – is not an easy task. In order to get sufficient accuracy, without overfitting requires a lot of training data. If you try to train a deep learning model from scratch, and hope build a classification system with similar level of capability of an ImageNet-level…

  • Milestones of Deep Learning

    Deep Learning has been around for about a decade now. We talked about how Deep Learning evolved through Artificial Intelligence, and Machine Learning (See “What is Deep Learning?“). Since its inception, Deep Learning has taken the world by storm due to its success. Here are some of the more significant achievements of Deep Learning throughout…

  • What is Deep Learning? – Updated

    What is Deep Learning? And, how does it relates to Machine Learning, and Artificial Intelligence? I did an article to answer these questions some time back. Now, thanks to the feedback I got from you all, I was able to updated it, with more clarifications, improved examples, and answers to more questions in Deep Learning.…

  • How deep should it be to be called Deep Learning?

    If you remember, some time back, I made an article on What is Deep Learning?, in which I explored the confusion that many have on terms Artificial Intelligence, Machine Learning, and Deep Learning. We talked about how those terms relate to each other: how the drive to build an intelligent machine started the field of…

  • Can the LeNet model handle Face Recognition?

    I recently followed a blog post – at PyImageSearch by Adrian Rosebrock – on using the LeNet Convolutional Neural Network model on the MNIST dataset – i.e. use for handwritten digit recognition – using Keras with Theano backend. I was able to easily try it out thanks to the very detailed and well thought out…

  • What is the image_dim_ordering parameter in Keras, and why is it important

    Update 9/May/2017: With Keras v2, the image_dim_ordering parameter has been renamed to image_data_format. Check my updated post on how to configure it. If you remember my earlier post about switching Keras between TensorFlow and Theano backends, you would have seen that we switched the image_dim_ordering parameter also when switching the backend. For TensorFlow, image_dim_ordering should…