Collaborating Authors

Computer Vision Meetup


Please don't hesitate to get in touch if you have a topic you'd like to talk about or a project you want to present! - [masked]:) Anyline is going to sponsor free drinks at the beginning of the evening. Agenda: 7pm: Grab a welcome drink 7.30pm: Is the Singularity near? Where technology and AI could lead us: Facts, forecasts and disruptive projections. A talk by Michael Sprinzl Abstract: Baseline detection is still a challenging task for heterogeneous collections of historical documents. We present a novel approach to baseline extraction in such settings, turning out the winning entry to the ICDAR 2017 Competition on Baseline detection (cBAD).

New AI computer vision system mimics how humans visualize and identify objects


The system is an advance in a type of technology called "computer vision," which enables computers to read and identify visual images. It is an important step toward general artificial intelligence systems -- computers that learn on their own, are intuitive, make decisions based on reasoning and interact with humans in a more human-like way. Although current AI computer vision systems are increasingly powerful and capable, they are task-specific, meaning their ability to identify what they see is limited by how much they have been trained and programmed by humans. Even today's best computer vision systems cannot create a full picture of an object after seeing only certain parts of it -- and the systems can be fooled by viewing the object in an unfamiliar setting. Engineers are aiming to make computer systems with those abilities -- just like humans can understand that they are looking at a dog, even if the animal is hiding behind a chair and only the paws and tail are visible.

Computer vision startup AnyVision pulls in new funding from Lightspeed


While there have been a few massive surveillance startups in China that have raised funds on the back of computer vision advances, there's seemed to be less fervor outside of that market. Tel Aviv-based AnyVision is aiming to leverage its computer vision chops in tracking people and objects to create some pretty clear utility for the enterprise world. After announcing a $27 million Series A in mid-2018, the computer vision startup is bringing Lightspeed Venture Partners into the raise, closing out the round at $43 million. "When you have a company with the technology AnyVision has, and the market need that I'm hearing from across industries, what you need to do is push the gas pedal and build an organization which can monetize and take on this opportunity to grow massively," Lightspeed partner Raviraj Jain told TechCrunch. Right now the 200-person company has its eyes on the security and identity markets as it aims to bring its computer vision technology into more industry-tailored solutions.

Internship Opportunities: Computer Vision


Microsoft Research provides a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers. Our researchers and engineers pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. It has never been a more exciting time at the Computer Vision Group at Microsoft Cloud & AI! We continue to advance the state of the art in the areas we choose to study. The Computer Vision Group is tasked to improve our odds of betting on the "next big thing" and impact various products in the areas of cloud and edge intelligence, such as Microsoft Cognitive Services and HoloLens.

Arduino Computer Vision Programming - Programmer Books


Most technologies are developed with an inspiration of human capabilities. Most of the time, the hardest to implement capability is vision. Development of highly capable computer vision applications in an easy way requires a generic approach. In this approach, Arduino is a perfect tool for interaction with the real world. Moreover, the combination of OpenCV and Arduino boosts the level and quality of practical computer vision applications.