TensorFlow TFRecord; Loading In and Popping Out Data (Part 1)

Considering the fact that I already had prior experience with training Neural Nets using MatConvNet, a Neural Networks toolbox available on MATLAB, I felt confident that training a CNN using TensorFlow would not be much of a hassle. To set my foot in, I started with some basic TensorFlow tutorials, including theTensorFlow CNN Guide. I was able to follow through the tutorial and saw my Convolutional Neural Network learn using the MNIST dataset. I was confident I now knew how to go about working with ConvNets on TensorFlow. Unfortunately, my confidence was brought to rubbles few weeks later when I wanted to use a raw dataset from the German Traffic Sign Recognition Benchmark (GTSRB). At this point, I discovered that the MNIST dataset we had used on the TensorFlow guide for CNN tutorial was a ready one. As a matter of fact, it was.............

My Deep Learning Journey; From Onlooker to MSc Thesis

On the afternoon of wednesday the 16th of November, 2016, I sat for a couple of hours in the renowned Edward Boyles Library of the University of Leeds, trying to craft a supervisory request email. A mail in which I had to convince my prospective supervisor to oversee my MSc project on the application of Deep Learning for Computer Vision in driverless cars. I did send the mail to him after spending about 8 hours putting together...............

Heterogeneous Computing; The Helpful Framework Behind Many Deep Learning Applications

As we know, ConvNets are a modified type of Multi Layer Perceptrons which make use of convolution layers for feature extraction. It has been proven that CPUs are not the best for convolution, and dedicated FPGA accelerators as well as GPUs do better with this kinds of operations. On the other hand, there exist a layer with most CNNs called the Softmax layer which helps to get the probability distribution of each output from a group of outputs from a ConvNet model. Conversely, It has been proven that CPUs are the best to perform this kind of operation. Similarly, where a bit of image processing need to be done such as in computer vision applications, we know that the GPU architecture is the best optimized for this kind of operaion. As such.....

What Makes ConvNets Different

When I first heard about Convolutional Neural Networks (ConvNets/CNNs), one of the puzzling questions I had to deal with was majorly around understanding the distinguishing factor(s) between them and the normal Multi Layer Perceptrons (MLP). Digging a bit deeper, I was able to grasp even more about what makes them peculiar. It is nothing extra/magical, but rather, its concept is embedded once again in a biologically inspired pipeline. This time, taking inspiration from the human visual cortex whose neurons get excited by........

Back Propagation: A Mathematical and Intuitive Explanation

Often times we hear about the backpropagation technique used during the training process of ANNs. At the snap of a finger, we can utilize backpropagation for Neural Nets Training on tools such as TesnorFlow, MATCOVNET, Caffe etc. For me, I decided to go a little bit deeper to understand what really goes on underneath. The backward propagation of errors or backpropagation, is a common method of training artificial neural networks and used in conjunction with an optimization method such as gradient descent. After the pioneering work of Rosenblatt and.......

The (Artificial) Neural Networks Framework; More Interesting Than You Think

Sometimes, when people hear titles like 'Artificial Neural Networks', 'Machine Learning', 'Deep Learning', 'Artificial Intelligence' etc, it comes accross to them as obscure concepts and probably a field requiring a lot of expertise, mathematics and statistical knowledge. While that is true, it is also true that we can start off learning in this area in a more simplistic manner. No rush into the maths and calculations, but rather, a little more verbal explanation on the philosophy behind some of these systems. This post is focused more on Neural Networks in general.......

The Future Leaders' Scholarship; My Chevening Experience

Chevening Scholarship Program, i.e., the UK Government’s international awards scheme aimed at developing global leaders started as far back as 1983 and ever since then, the UK government has maintained consistency in identifying potential leaders from over 160 countries and territories, yearly. Essentially, the Chevening Scholarship Program is one of the UK’s foreign agenda to forge early alliances with potential leaders.....