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Deep learning has been very successful when working with images as data and is currently at a stage where it works better than humans on multiple use-cases. The most important problems that humans have been interested in solving with computer vision are image classification, object detection and segmentation in the increasing order of their difficulty. In the plain old task of image classification

The amount of data being collected is drastically increasing day-by-day with growing numbers of applications, software, and online platforms. To handle/access this humongous data productively, it’s necessary to develop valuable information extraction tools. One of the sub-areas that’s demanding attention in the Information Extraction field is the extraction of tables from images or the detection o

We live in times when any organization or company to scale and to stay relevant has to change how they look at technology and adapt to the changing landscapes swiftly. We already know how Google has digitized books. Or how Google earth is using NLP (or NER) to identify addresses. Or how it is possible to read text in digital documents like invoices, legal paperwork, etc. But how does it work exact

Published: Jul 19, 2019 ● Updated: Mar 27, 2024 IntroductionWhile I do not like getting pulled over by cops any more than you do, I can't deny that having cameras that can track and count the vehicles passing by attached to traffic lights might just do some good for society. Computers are getting better everyday at thinking, analyzing situations and making decisions like humans do. Understanding v

OCR provides us with different ways to see an image, find and recognize the text in it. When we think about OCR, we inevitably think of lots of paperwork - bank cheques and legal documents, ID cards and street signs. In this blog post, we will try to predict the text present in number plate images. What we are dealing with is an optical character recognition library that leverages machine learning

Uncover valuable insights from any document and automate repetitive tasks, with AI-powered workflows.

Home Artificial Intelligence Data Augmentation | How to use Deep Learning when you have Limited Data — Part 2 This article is a comprehensive review of Data Augmentation techniques for Deep Learning, specific to images. This is Part 2 of How to use Deep Learning when you have Limited Data. Checkout Part 1 here. We have all been there. You have a stellar concept that can be implemented using a mach

How to do Semantic Segmentation using Deep learning semantic segmentation is one of the key problems in the field of computer vision. This article is a comprehensive overview including a step-by-step guide to implement a deep learning image segmentation model. This article is a comprehensive overview including a step-by-step guide to implement a deep learning image segmentation model. We shared a

How to easily Detect Objects with Deep Learning on Raspberry Pi This post demonstrates how you can do object detection using a Raspberry Pi. Like cars on a road, oranges in a fridge, signatures in a document and teslas in space. The real world poses challenges like having limited data and having tiny hardware like Mobile Phones and Raspberry Pis which can’t run complex Deep Learning models. This p