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Mineralogy and optical mineralogy

By: Contributor(s): Publication details: Mineralogical Society of America 2008 ChantillyDescription: xxiv, 708pISBN:
  • 9780939950812
Subject(s): DDC classification:
  • 006.31 D981m
Summary: Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks, and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection, and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Deep learning is at the heart of artificial intelligence, and achievements and errors in the field are driving a great and constant interest.
List(s) this item appears in: New arrivals March 10 to 16, 2025
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Text Books Text Books PK Kelkar Library, IIT Kanpur TEXT 006.31 D981m (Browse shelf(Opens below)) Available A186824
Total holds: 0

Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks, and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection, and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Deep learning is at the heart of artificial intelligence, and achievements and errors in the field are driving a great and constant interest.

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