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Quality and Cost Trade-offs in Passage Re-ranking Task
Deep learning models named transformers achieved state-of-the-art results in a vast majority of NLP tasks at the cost of increased computational complexity and high memory consumption.
One-Shot Learning with Triplet Loss for Vegetation Classification Tasks
The average accuracy for plant disease detection amounted to over 97. 8% and 97. 6% for moss species classification.
The particle track reconstruction based on deep learning neural networks
One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction.
Catch and Prolong: recurrent neural network for seeking track-candidates
One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction.
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