Recent advancement in the field of deep learning has enabled us to develop models that yield impressive results across various fields, from image classification, object detection, to speech recognition. However, developing the architecture for each problem is a challenge in itself. In this paper, the authors present a single deep Continue Reading
Computer Vision
What is Data Augmentation?
Data augmentation is a process that enables you to increase the amount of training data by making reasonable modifications in your existing data. It helps you to increase the diversity of your training data which is essential for developing a robust model. This then, generally speaking, improves the performance of Continue Reading
Unet Segmentation in TensorFlow
In recent years deep learning is a huge success in the world of computer vision, making deep learning the new tool in the digital image analysis. It has made computers understand the visual data much better than ever before. In this article, I’ll go into details about one specific task in computer vision: Semantic Segmentation using the UNET Architecture.
Dog Breed Classification using Transfer Learning in TensorFlow
In this article, we will go through the TensorFlow to build a Convolutional Neural Network that will help you to identify the breed of a dog from its image. In the process, we will use Transfer Learning and learn how to design, train and test models with the provided dataset.