Examples of using Recognition algorithm in English and their translations into Greek
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Computer
I can run a pattern recognition algorithm.
Face Recognition algorithm(Optional).
High-precision face recognition algorithm.
Speech recognition algorithms are similarly vulnerable.
Probably using facial recognition algorithms.
People also translate
Speech recognition algorithms are supposed to do the rest.
Todd's been working on this really cool facial recognition algorithm.
Fingerprint recognition algorithm is superior.
Scientists have named they have developed a technology FRAME(Frequency Recognition Algorithm for Multiple Exposures).
Recognition algorithms aren't just limited to facial expressions.
It is called FRAME(Frequency Recognition Algorithm for Multiple Exposures).
Unique face recognition algorithm to accurately recognize faces, face recognition time<500ms.
The technology is called as Frequency Recognition Algorithm for Multiple Exposures(FRAME).
The front-end recognition algorithm is integrated with the camera, the camera directly The output has car-free results.
The researchers call the technology FRAME- Frequency Recognition Algorithm for Multiple Exposures.
Alibaba's speech recognition algorithm can isolate voices in noisy crowds.
The camera is installed in front of the parking space to capture the image, and the vehicle license plate recognition algorithm determines whether the vehicle has the parking space information.
Adpots X-face V4.0 recognition algorithm, featuring fast recognition and low error rate.
The researchers have named the technology Frequency Recognition Algorithm for Multiple Exposures, or FRAME.
A newly developed object recognition algorithm achieves real-time high-speed processing of spatial information consisting of color, pattern(brightness level), and subject distance(depth).
Real-time Tracking is available as well,which utilizes a newly developed subject recognition algorithm to ensure the ultimate subject tracking and persistence of the focusing system.
A newly developed subject recognition algorithm processes spatial information based on color, subject distance(depth), pattern(brightness), and face and eye information at high speed in real time.
Additionally, the Real-time Trackingvii feature is available which utilises a newly developed subject recognition algorithm to ensure the ultimate subject tracking and persistence of the focusing system.
The new technology called Frequency Recognition Algorithm for Multiple Exposures(FRAME) is based on an innovative algorithm, and instead captures several coded images in one picture.
Facial recognition Traditional face recognition algorithms are based on local features.
The new technology called Frequency Recognition Algorithm for Multiple Exposures(FRAME) is based on an innovative algorithm, and instead captures several coded images in one picture and later sorts them into a video sequence.
When you're tracking a fast-moving subject,the camera's improved automatic subject motion tracker uses a newly developed subject recognition algorithm that draws on color, pattern(brightness), subject distance(depth) and face/eye information to recognize, and hold onto, your subject.
Traditional face recognition algorithms are based on local features.
In 2015, researchers at Google modified a deep-learning-based image recognition algorithm so that instead of spotting objects in photos, it would generate or modify them.
Then they will run a recognition algorithm on just the pixels inside each rectangle.