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Fekhr Eddine Keddous and Amir Nakib
Convolutional neural networks (CNNs) have powerful representation learning capabilities by automatically learning and extracting features directly from inputs. In classification applications, CNN models are typically composed of: convolutional layers, po...
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Chartwut Thanajiranthorn and Panida Songram
Associative classification (AC) is a mining technique that integrates classification and association rule mining to perform classification on unseen data instances. AC is one of the effective classification techniques that applies the generated rules to ...
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Vincent Gripon, Matthias Löwe and Franck Vermet
Nearest neighbor search is a very active field in machine learning. It appears in many application cases, including classification and object retrieval. In its naive implementation, the complexity of the search is linear in the product of the dimension a...
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Roman Kaplan,Leonid Yavits,Ran Ginosar
Pág. 99 - 116
Near-data in-memory processing research has been gaining momentum in recent years. Typical processing-in-memory architecture places a single or several processing elements next to a volatile memory, enabling processing without transferring data to the ho...
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V. O. Pashchenko,N. O. Matvieieva
Pág. 172 - 175
The neural networks with associative memory have been proposed to estimate the size of surface solidness defect of current-conducting material (article) with the help of the increases of electromagnetic probing impulse area (average amplitude).
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