Innovative Topologies and Algorithms for Neural Networks
The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text process...
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| Format: | Online |
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| Jezik: | engleski |
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MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Teme: | |
| Online pristup: | ONIX_20210501_9783036502847_287 |
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| _version_ | 1869519279150333952 |
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| collection | Directory of Open Access Books |
| description | The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks has been devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. This book gives significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications. |
| format | Online |
| id | doab-20.500.12854ir-68541 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-685412024-03-30T12:51:06Z Innovative Topologies and Algorithms for Neural Networks Xibilia, Maria Gabriella Graziani, Salvatore facial image analysis facial nerve paralysis deep convolutional neural networks image classification Chinese text classification long short-term memory convolutional neural network Arabic named entity recognition bidirectional recurrent neural network GRU LSTM natural language processing word embedding CNN object detection network attention mechanism feature fusion LSTM-CRF model elements recognition linguistic features POS syntactic rules action recognition fused features 3D convolution neural network motion map long short-term-memory tooth-marked tongue gradient-weighted class activation maps ship identification fully convolutional network embedded deep learning scalability gesture recognition human computer interaction alternative fusion neural network deep learning sentiment attention mechanism bidirectional gated recurrent unit Internet of Things convolutional neural networks graph partitioning distributed systems resource-efficient inference pedestrian attribute recognition graph convolutional network multi-label learning autoencoders long-short-term memory networks convolution neural Networks object recognition sentiment analysis text recognition IoT (Internet of Thing) systems medical applications thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks has been devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. This book gives significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications. 2021-05-01T15:12:16Z 2021-05-01T15:12:16Z 2021 book ONIX_20210501_9783036502847_287 9783036502847 9783036502854 https://directory.doabooks.org/handle/20.500.12854/68541 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/3562 https://mdpi.com/books/pdfview/book/3562 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-0285-4 10.3390/books978-3-0365-0285-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036502847 9783036502854 198 Basel, Switzerland open access |
| spellingShingle | facial image analysis facial nerve paralysis deep convolutional neural networks image classification Chinese text classification long short-term memory convolutional neural network Arabic named entity recognition bidirectional recurrent neural network GRU LSTM natural language processing word embedding CNN object detection network attention mechanism feature fusion LSTM-CRF model elements recognition linguistic features POS syntactic rules action recognition fused features 3D convolution neural network motion map long short-term-memory tooth-marked tongue gradient-weighted class activation maps ship identification fully convolutional network embedded deep learning scalability gesture recognition human computer interaction alternative fusion neural network deep learning sentiment attention mechanism bidirectional gated recurrent unit Internet of Things convolutional neural networks graph partitioning distributed systems resource-efficient inference pedestrian attribute recognition graph convolutional network multi-label learning autoencoders long-short-term memory networks convolution neural Networks object recognition sentiment analysis text recognition IoT (Internet of Thing) systems medical applications thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Innovative Topologies and Algorithms for Neural Networks |
| title | Innovative Topologies and Algorithms for Neural Networks |
| title_full | Innovative Topologies and Algorithms for Neural Networks |
| title_fullStr | Innovative Topologies and Algorithms for Neural Networks |
| title_full_unstemmed | Innovative Topologies and Algorithms for Neural Networks |
| title_short | Innovative Topologies and Algorithms for Neural Networks |
| title_sort | innovative topologies and algorithms for neural networks |
| topic | facial image analysis facial nerve paralysis deep convolutional neural networks image classification Chinese text classification long short-term memory convolutional neural network Arabic named entity recognition bidirectional recurrent neural network GRU LSTM natural language processing word embedding CNN object detection network attention mechanism feature fusion LSTM-CRF model elements recognition linguistic features POS syntactic rules action recognition fused features 3D convolution neural network motion map long short-term-memory tooth-marked tongue gradient-weighted class activation maps ship identification fully convolutional network embedded deep learning scalability gesture recognition human computer interaction alternative fusion neural network deep learning sentiment attention mechanism bidirectional gated recurrent unit Internet of Things convolutional neural networks graph partitioning distributed systems resource-efficient inference pedestrian attribute recognition graph convolutional network multi-label learning autoencoders long-short-term memory networks convolution neural Networks object recognition sentiment analysis text recognition IoT (Internet of Thing) systems medical applications thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | facial image analysis facial nerve paralysis deep convolutional neural networks image classification Chinese text classification long short-term memory convolutional neural network Arabic named entity recognition bidirectional recurrent neural network GRU LSTM natural language processing word embedding CNN object detection network attention mechanism feature fusion LSTM-CRF model elements recognition linguistic features POS syntactic rules action recognition fused features 3D convolution neural network motion map long short-term-memory tooth-marked tongue gradient-weighted class activation maps ship identification fully convolutional network embedded deep learning scalability gesture recognition human computer interaction alternative fusion neural network deep learning sentiment attention mechanism bidirectional gated recurrent unit Internet of Things convolutional neural networks graph partitioning distributed systems resource-efficient inference pedestrian attribute recognition graph convolutional network multi-label learning autoencoders long-short-term memory networks convolution neural Networks object recognition sentiment analysis text recognition IoT (Internet of Thing) systems medical applications thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20210501_9783036502847_287 |