Becoming a Computer Vision Engineer in 2021
Becoming a Computer Vision Engineer in 2021

If you want to dig into Computer Vision (CV) but have no idea where to start, this beginner guide is for you. Here we recommend some sources which will come in handy for learning and understanding both the computer vision and deep learning basics.

4 Ways How Computer Vision Is Deepening the Fashion Industry
4 Ways How Computer Vision Is Deepening the Fashion Industry

What is your first thought when you hear about computer vision (CV) in fashion? Or, what is the first thing that pops into your head when you hear about deep learning fashion? Let us guess – online clothing shopping or virtual try-on applications? Well, this might be surprising but deep fashion is not a far future anymore.

Computer Vision in Healthcare
Computer Vision in Healthcare

Artificial intelligence (AI) and machine learning (ML) are being progressively used across different sectors including healthcare. One of the AI-powered tools is computer vision (CV), the ability to recognize, interpret, and process visual data. Thus, potential applications of computer vision in the medical field are multifold, from image processing and predictive analysis to automated health records. All this enables improving the quality of delivered medical services and the healthcare administration system.

Applications of Artificial Intelligence in Automotive Industry
Applications of Artificial Intelligence in Automotive Industry

A century ago, the very thought of machines being able to think, make complicated calculations, and come up with effective solutions to pressing problems was more of a figment of science fiction writer’s fantasy rather than a foreseeable reality.

Embedded and Single-Board Computer Vision: Running Deep Neural Nets
Embedded and Single-Board Computer Vision: Running Deep Neural Nets

Deep learning (DL) and neural networks are extremely widespread in different computer vision (CV) applications. Indeed, many typical problems (like object recognition or semantic segmentation) are effectively solved by the convolutional neural networks (CNNs). In this article, we are going to discuss how to utilize CNNs on embedded devices.

Embedded and Single-Board Computer Vision: Introduction
Embedded and Single-Board Computer Vision: Introduction

Computer vision (CV) and machine learning (ML) algorithms solve a tremendous amount of problems. However many businesses often do not understand what hardware to choose for running your favorite neural net or some advanced image and video processing pipelines. With this blog post, we start a series of articles about embedded vision and specific practical things you need to know before making your choice.

SDK for Augmented Reality Applications
SDK for Augmented Reality Applications

Our client’s goal was to enhance various printed media (magazines, posters, banners, etc.) with interactive experience using augmented reality. With AR, certain areas on the reading materials can be overlayed with digital information of a different kind: from videos, images, and 3D models to weather information and buttons that bring additional functionality, etc.

Page Unwrapper
Page Unwrapper

The task of automatic document analysis and recognition is very common in everyday life. Basically, every time when a user needs to automatically parse and recognize some content from a picture captured with a mobile phone/tablet or a scanned document – for example, text, tables, links, etc., automatic document recognition and text analysis come to the stage.

Binary Marker Recognition on Raspberry
Binary Marker Recognition on Raspberry

Fiducial markers are widely used in various applications like robot navigation, logistics, augmented reality. Fig. 1. Applications of fiducial markers Advantages are obvious High contrast Simple code generation Resistance to extremal angles However, when we deal with a large number of markers, real-time recognition becomes challenging, especially on embedded devices with low power CPUs on-board.

Automatic number plate recognition (ANPR) systems
Automatic number plate recognition (ANPR) systems

Currently, the number of cars in the world is well over 1 billion. It is no wonder that one of the most common computer vision tasks is the effective control of these vehicles through automatic number plate recognition (ANPR) systems.