Examples of using Image recognition in English and their translations into German
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PageManager, Digital Image Recognition Presto!
Image recognition and self-learning software evaluate the data.
I include a section on subliminal image recognition, where you'll.
Programmed image recognition For a 1986 dodge coronet.
A good example of a machine that'sbeen trained in this way is Google's image recognition AI.
De, the technology is showing"impressive image recognition capabilities, especially in poor conditions.
Image recognition thus saves time and sample materials, which directly benefits both the patient and the doctor.
Deep learning has led to breakthroughs in image recognition and language processing.
Image recognition and processing is one of the sectors in automation of logistic processes relevant to success.
It is primarily intended to support image recognition and was developed by the Chinese start-up Cambricon.
Once entered in Evernote, your handwritten notes can then be edited andsearched using image recognition technology.
Or take automatic image recognition, which Google is now using heavily and which allows for new business models.
The smart glasses by AiServe helps visually impaired people orientate with voice control andautomatic image recognition in their daily life.
Revolutionary"image recognition" becomes your virtual guide, interactively delivering you a unique multimedia experience.
Since the actual artists cultivate an inimitable style,scientists at the Rutgers University are using image recognition methods to track down most of the counterfeiters.
Through fastest image recognition via a 5G solution and position calculations in the Cloud backend, the Carrera cars were complemented with additional graphics e. g.
In fact, there are already impressive examples of applications with artificialintelligence, for example in medical image recognition for tumor analysis.
Today many applications used in daily life, such as image recognition and recommendation systems, incorporate sophisticated AI-supported components.
Deep Learning is a new information processing method based on artificial neuralnetworks which has led to ground-breaking achievements in image recognition, speech processing and robotics.
As good as the counterfeiters can deceive the human eye, the image recognition learned to distinguish the fakes from the originals by the very own stroke of the artists.
For optimized production control of processes in the tireindustry, artificial intelligence methods are used to learn the test and validation data required for automatic image recognition.
The same applies to visual recognition- fully automatic image recognition is used so that driverless transport systems can control themselves independently and scan barcodes.
Augmented reality(AR) superimposed text or graphics on images seen in smartphones, tablets and screens of personal computers or through special glasses,allowing features such as image recognition.
Steps to an AI Proof of Concept Afive-step approach to success with proof of concepts(PoC) for image recognition, natural language, and predictive maintenance.
The Ricoh SC-10 combines a camera, image recognition, and control into a self-contained, compact unit that can help to prevent errors in manual assembly operations.
Intelligent driving assistants, autonomous driving and braking, smart image recognition and real-time mapping- these and other modern innovations will be demonstrated live by various manufacturers in the outdoor area.
Forward-looking sensors in combination with advanced image recognition and processing allows the Phantom 4 active obstacle avoidance, which allows the drone to avoid objects on their way.
The COSIR project(combination of chemical-optical sensors and image recognition), which is backed by the Bavarian Research Foundation, is tackling an important challenge in the field of cell cultivation in the laboratory.
Today deep neural networks- a leading-edge form of machine learning-have been used for image recognition, video and natural language processing, and for understanding all the complex visual cues necessarily for autonomous driving.
How can a combination of machine learning, language and image recognition transform translations into an interactive game and digital communication into an audiovisual experience, and how can it support farmers in the analysis of plants and soils?