We’ve got a lot of great ideas for running AI/XR solutions on a mobile device, and our team needs a strong iOS developer to bring them to life.


We’ve got a lot of great ideas for running AI/XR solutions on a mobile device, and our team needs a strong iOS developer to bring them to life.

This blog post covers some important aspects of deploying and running classical computer vision algorithms as well as convolutional neural networks in a web front-end. Please make sure you have read the first part of the blog post. This will definitely help you to follow all technical aspects much easier. How can you pass an image or a video frame from JS to C++ and back? We’ll give a minimal example.

Are you interested in Computer Vision (CV)? Probably yes, if you are reading this. If you read CV tutorials, you might have noticed that most of them are in Python. This applies to both traditional CV (without neural networks) and, even more, to deep learning (neural networks). Occasionally, CV tutorials use C++ instead of Python, but any other programming languages are very rare.

Surprising but true: according to market research, customers prefer apples with a maximum diameter of 75 to 80 mm 🍏 Now you know 🙂 People would obviously struggle to accurately evaluate fruits’ size with their naked eyes. In contrast, computer vision (CV) systems can measure the precise diameter of an apple in the blink of an eye, literally. CV systems can collect and process a variety of parameters, including size, weight, shape, texture, color, and much more.

Another summer, another edition of our internship on computer vision to be proud of! This time we received well over 100 applications from more than 20 cities including Kyiv, Kharkiv, Lviv, Dnipro, Odesa, Mykolaiv, Vinnytsia, Uzhhorod, Poltava, Kremenchuk, Sumy, Zaporizhzhia, Kryvyi Pih, and Mariupol. What an impressive geography! Only three of the applicants made it to the ‘finals’.

Want to know what stands behind remote photoplethysmography (rPPG) and how to non-invasively monitor vital parameters such as heart rate and respiration, oxygen saturation, and blood pressure using just a phone camera? During the event, our CEO Ievgen Gorovyi will dive into the details of developing a computer vision-based solution for such healthcare application. 📅 Join us on September 18 at 11:00 in Zoom meeting! 🎯 Participation is free by pre-registration 👉🏻 https://cutt.ly/mWT8uv0.

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.

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.

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.

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.