Examples of using Computer vision algorithms in English and their translations into Chinese
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Computer vision algorithms correct and standardize the image, and, as with Dip.
OpenCV for Python enables us to run computer vision algorithms in real….
Computer vision algorithms can't touch the physical world, they can just look at it.
That's not all Google Lens' computer vision algorithms can recognize, of course.
Computer vision algorithms can enable home security camera to become more efficient in the usage of these resources.
Across several industry benchmarks, our computer vision algorithms have surpassed others in the industry- even humans.
That project included tracking down 50,000images of coffee mugs on which to train the robot's computer vision algorithms.
Now, with AI and computer vision algorithms, it's fully automatic and free of human error.”.
With the release of the Vision framework,developers can now use this technology and many other computer vision algorithms in their apps.
Even the most powerful computer vision algorithms today are able to make only the most basic sense of images.
We could build an autonomous killing drone today with a consumer-grade drone,a robotic gun trigger and computer vision algorithms downloaded from GitHub.
Most computer vision algorithms need to be fed lots of labelled images so it can tell different objects apart.
ViSenze utilizes machine learning and computer vision algorithms, which process and analyze millions of visual content.
Computer vision algorithms that could potentially pinpoint relevant patient populations through a range of inputs from handwritten forms to digital medical imagery.
Across several industry benchmarks, our computer vision algorithms have surpassed others in the industry- even humans.
Computer vision algorithms are naturally adept at spotting anomalies experts sometimes miss, in the process reducing wait times and lightening clinical workloads.
When you upload photos in Google Photos, it uses its computer vision algorithms to annotate them with content information about scenes, objects, and persons.
Computer vision algorithms that could potentially determine appropriate patient populations through a variety of inputs from handwritten forms to digital medical imagery.
When you upload photos in Google Photos, it uses its computer vision algorithms to annotate them with content information about scenes, objects, and persons.
These computer vision algorithms needed to be complemented with higher-level tools of analysis involving knowledge representation and reasoning, often under conditions of uncertainty.
This makes the R-Car V3M and V3H suitable for computer vision algorithms, like object detection& classification, deep neural networks, and convolutional neural networks.
The system uses computer vision algorithms to extract important features from an image, such as the position of the cell walls.
With the advent of high performance general purpose computer vision algorithms, the accurate automated analysis of chest radiographs is becoming increasingly of interest to researchers.
For example, computer vision algorithms are excellent at making sense of visual information but cannot translate and apply that ability to other tasks.
In some cases, well-trained computer vision algorithms can perform on par with humans that have years of experience and training.
For example, computer vision algorithms are excellent at making sense of visual information but cannot translate and apply that ability to other tasks.
In some cases, well-trained computer vision algorithms can perform on par with humans that have years of experience and training.
Before deep learning, creating computer vision algorithms that could process medical images required extensive efforts from software engineers and subject matter experts.