In 2019, we placed our bet on AI being the future. By strategically investing in emerging technologies early on, we wanted to gain a competitive advantage and establish ourselves as industry leaders before our competitors.
Machine Can See LLC was founded by two founders.
As one of the most promising tech startups in Serbia, Machine Can See has secured an equity−free pre−seed investment of 115k euros from the Republic of Serbia's Innovation Fund.
Machine Can See reached a significant milestone by hiring its first employees. With the addition of the first employees, Machine Can See was able to accelerate its growth and expand its product offerings.
The whitepaper proposes a solution to the issue of parking occupancy in outdoor lots and street parking spots using Computer Vision (CV) algorithms and Smart Edge devices. The proposed solution utilizes new data streams to construct a 3D model of the parking environment, accurately identifying available on-street parking spaces with high precision.
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Out of 124 applicants, we were one of the 27 startups chosen to participate. This opportunity provided valuable exposure and resources to advance our mission of bringing Visual AI solutions to smart cities and promoting sustainability.
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Machine Can See's patent aims to improve object prediction using camera images, focusing on objects like transportation means, buildings, and roads. The system uses a vector model of the object created through the neural network, which is placed in a database and used to generate a 3D simulation of the space viewed.
By incorporating physics models, the system achieves higher accuracy and realism, leading to more precise predictions of real-life situations.
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We successfully achieved the milestone of having a prototype ready. Through rigorous testing and iteration, we were able to refine and improve the prototype, ensuring that it was ready for the next phase of development.
This achievement was a significant step forward for our company and brought us closer to our ultimate goal of delivering a high−quality product to our customers.
This whitepaper explores how to determine the 3D orientation of an object in computer vision using a new approach. It suggests using Euler angles and two coordinate systems to represent the object's orientation in 3D space, and generating a visual bounding box using computer−generated images. The paper also mentions using quaternions for rotating the 3D bounding box in the algorithm.
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Landing our first big paying client from the US is a significant milestone for our company, as it demonstrates the viability of our concept and the potential for our product in the oil and energy industry.
This project is a big and long undertaking, and we are thrilled to be reaching this point.
MCS is a technology company that specializes in computer vision, artificial intelligence, smart city technology, traffic management, parking solutions, and the Internet of Things (IoT).
Our team has a successful track record in developing and overseeing projects, and we bring expertise in a wide range of fields, including software development, machine learning, and game development. We have a proven record of delivering successful projects in these areas, and we're dedicated to helping our clients achieve their goals through innovative technology solutions.
to advisors who have vast experience in the fields of Visual AI and Neural Networks.
Dubravko, who is a Professor of Information and Communication Systems at the University of Novi Sad, Serbia, has a Ph.D. degree in Computer Engineering from the Florida Atlantic University, Boca Raton, USA.
In addition to conducting scientific research in the domain of Visual AI and Neural Networks for the last 21 years, he is a Tandemlaunch deep−tech foundry and an NVIDIA Deep Learning Institute University Ambassador.
Dubravko is now the acting director of The Artificial Intelligence Research and Development Institute of Serbia.
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