Examples of using Deep learning algorithm in English and their translations into Indonesian
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The deep learning algorithm requires a lot less time to operate.
This is because there are so many parameters in a deep learning algorithm that training them takes longer than usual.
Latest deep learning algorithm boosts products' false alarm reduction capability to 98% accuracy.
Kngine develops mobile solutions thatuse AI to respond to questions using its deep learning algorithm.
In a similar way, deep learning algorithms can automatically translate between languages.
Air has developed several times in the last fewyears due to the powerful machine learning and deep learning algorithm.
RankBrain is a deep learning algorithm performing unsupervised learning. .
Siemion gave Yunfan“Gerry” Zhang, a doctoral student at Berkeley,the job of training a deep learning algorithm to hunt for the additional bursts.
These deep learning algorithms can be applied to unsupervised learning tasks.
Bidirectional Encoder Representation from Transformers(BERT) is the deep learning algorithm that relates to natural language processing.
AlphaGo, the deep learning algorithm that beat Lee Sedol at the game of Go in 2016, is fundamentally different.
The BERT algorithm(Bidirectional Encoder Representations from Transformers) is a deep learning algorithm related to natural language processing.
With the deep learning algorithm on Synology NAS, random photos are automatically grouped together according to similar faces, subjects, and places.
By giving instructions about what to look for,the scientists were able to train the deep learning algorithm to assess the PET images for early signs of Alzheimer's.
In this technology, a deep learning algorithm is applied to the photo of the face or the facial features and then, a list of probable syndromes is produced.
A Neural Processing Unit(NPU)is a processor that is optimized for deep learning algorithm computation, designed to efficiently process thousands of these computations simultaneously.
The deep learning algorithm has been trained with about 2 million adult and child patients admitted to either the Stanford Hospital or Lucile Packard Children's hospital to predict the mortality of a given patient within the next three to 12 months.
Researchers said the photos were then digitized andused to train a deep learning algorithm so that it could distinguish cervical conditions requiring treatment from those not requiring treatment.
The researchers trained a deep learning algorithm on the Electronic Health Records of about 2 million adult and child patients admitted to either the Stanford Hospital or Lucile Packard Children's hospital to predict the mortality of a given patient within the next three to 12 months.
Just like how we learn from experience, the deep learning algorithm repeatedly performs a task, every time it is modified to enhance the outcome.
Using an industry-leading deep learning algorithm, combined with neural network technology, your Y95 can identify objects and scenes in your photos and perform related searches.
Similar to how humans learn from experience, a deep learning algorithm performs a task repeatedly, each time tweaking it slightly to improve the outcome.
The researchers developed and applied a deep learning algorithm that used the smartphone-based PPG signal recordings from participants to identify which patients had diabetes based on this signal alone.
The technology works by applying the deep learning algorithm to the facial characteristics of the image provided, then producing a list of possible syndromes.
Just like we learn from experience, the deep learning algorithm would perform a task repeatedly, each time making fine adjustments to improve the outcome.
Similarly, to how we learn from experience, the deep learning algorithm would perform a task repeatedly, each time tweaking it a little to improve the outcome.
Similar to how humans learn from experience, the deep learning algorithm would perform a task repeatedly, each time tweaking it a little to obtain an improved outcome.
The photos were digitised and then used to train a deep learning algorithm so that it could distinguish cervical conditions requiring treatment from those not requiring treatment.
The photos were digitized and used to train a deep learning algorithm so that it could distinguish between the cervical conditions requiring treatment and those not requiring treatment.