Fill your Computer Vision jobs quickly and easily

Computer Vision is probably one of the most exciting fields in the sector of Artificial Intelligence. Analogous to the human sense of sight, a computer learns to automatically find, process and interpret useful information in images or video material. Especially due to the use of neural networks and advances in deep learning, more and more companies rely on Computer Vision to solve various problems. One technology driver is the automotive industry, which needs the technology to develop self-propelled cars. But Computer Vision is also used today in quality assurance in manufacturing companies or the inspection of industrial plants. As a personnel consultancy in the field of IT and technologies of the future, PALTRON has built up years of experience in filling expert positions. From highly qualified post-docs to specialized Computer Vision Engineers. We will find your expert or a whole team!

Machines see more than humans

Computer Vision simulates the human ability to perceive the environment, to distinguish different objects and to name them with a certain probability. Meanwhile, artificial neural networks are almost exclusively used for this purpose. Using labeled training data sets, these networks learn to recognize different objects from all possible perspectives.

This training is one of the main problems in the field of computer vision. Similar to humans - who, thanks to their evolutionary experience, already distinguish between different objects in childhood - a neural network requires gigantic data sets in order to recognize an object with a high probability. This is why more and more companies are relying on artificially generated data sets to train their neural networks.

Today, image recognition mainly uses convolutional neural networks (CNN). These are able to generate information from image data. However, these networks are not able to set the image data in a temporal relation. Therefore, Recurring Neural Networks (RNN) are used for the evaluation of video material which can connect different frames with each other.

Due to the enormous progress in this field, it is now not only possible to place a box around an object in the image (object detection). Rather, each pixel of an image can be assigned to an object (semantic segmentation). Fully Convolutional Networks (FCN) are used for this purpose. Mask R-CNN networks go one step further. These decompose image data into their most fundamental blocks and are thus able to distinguish all individual persons, e.g. in a group of people.

As a leading personnel consultancy in the field of artificial intelligence, we find your expert for computer vision. Whether in the field of autonomous driving, drones detection, scratch and hairline crack detection, medical technology or in quality assurance, we assist with our digital know-how!

Your contact persons

Josef Günthner

Josef Günthner

Co-founder & Managing Director

contact@paltron.com

+49 (0) 40 180 241 180

Daniel Wernicke

Daniel Wernicke

Managing Director

contact@paltron.com

+49 (0) 40 180 241 180

Verena Netscher

Verena Netscher

Director

contact@paltron.com

+49 (0) 40 180 241 180

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