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US$ 75.35
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US$ 79.12
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Hardcover. Condition: new. Hardcover. There is a large amount of data from different types of sensors, for instance, multispectral electro-optical/infrared (EO/IR) and computed tomography/magnetic resonance (CT/MR) images, among others. How to take advantage of multimodal data for object detection and pattern recognition is an active field of research. Information fusion (IF) is used for enhancing the performance of pattern classification, while deep learning (DL) technologies, including convolutional neural networks (CNNs), are powerful tools for improving object detection, segmentation, and recognition. It is viable to combine DL and IF to boost the overall performance of pattern classification and target recognition. Such combinations of powerful techniques may exploit the deeply hidden features of the multimodal, spatial, or temporal data. This reprint presents cutting-edge research utilizing DL and IF techniques. Key research areas include image and video analysis, covering topics such as super-resolution, object detection, semantic segmentation, video captioning, and text processing, including labeling enhancement and screening misinformation. Biometric applications explore innovations in human identification using facial and finger vein recognition, facial micro-expression analysis, and fatigue detection. Advanced applications extend to handwritten recognition, tracking supermarket customer behavior, parcel sorting, predicting road surface conditions, and plastic waste classification. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Magnesium Alloys as Degradable Biomaterials
Published by Taylor & Francis Ltd, 2020
ISBN 10: 0367575507 ISBN 13: 9780367575502
Language: English
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US$ 73.27
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Magnesium Alloys as Degradable Biomaterials
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Deep Learning for Information Fusion and Pattern Recognition
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Magnesium Alloys As Degradable Biomaterials
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Magnesium Alloys As Degradable Biomaterials
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US$ 110.73
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Add to basketPaperback. Condition: Brand New. 600 pages. 9.21x6.14x1.26 inches. In Stock.
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Add to basketHardcover. Condition: new. Hardcover. There is a large amount of data from different types of sensors, for instance, multispectral electro-optical/infrared (EO/IR) and computed tomography/magnetic resonance (CT/MR) images, among others. How to take advantage of multimodal data for object detection and pattern recognition is an active field of research. Information fusion (IF) is used for enhancing the performance of pattern classification, while deep learning (DL) technologies, including convolutional neural networks (CNNs), are powerful tools for improving object detection, segmentation, and recognition. It is viable to combine DL and IF to boost the overall performance of pattern classification and target recognition. Such combinations of powerful techniques may exploit the deeply hidden features of the multimodal, spatial, or temporal data. This reprint presents cutting-edge research utilizing DL and IF techniques. Key research areas include image and video analysis, covering topics such as super-resolution, object detection, semantic segmentation, video captioning, and text processing, including labeling enhancement and screening misinformation. Biometric applications explore innovations in human identification using facial and finger vein recognition, facial micro-expression analysis, and fatigue detection. Advanced applications extend to handwritten recognition, tracking supermarket customer behavior, parcel sorting, predicting road surface conditions, and plastic waste classification. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketHardcover. Condition: new. Hardcover. There is a large amount of data from different types of sensors, for instance, multispectral electro-optical/infrared (EO/IR) and computed tomography/magnetic resonance (CT/MR) images, among others. How to take advantage of multimodal data for object detection and pattern recognition is an active field of research. Information fusion (IF) is used for enhancing the performance of pattern classification, while deep learning (DL) technologies, including convolutional neural networks (CNNs), are powerful tools for improving object detection, segmentation, and recognition. It is viable to combine DL and IF to boost the overall performance of pattern classification and target recognition. Such combinations of powerful techniques may exploit the deeply hidden features of the multimodal, spatial, or temporal data. This reprint presents cutting-edge research utilizing DL and IF techniques. Key research areas include image and video analysis, covering topics such as super-resolution, object detection, semantic segmentation, video captioning, and text processing, including labeling enhancement and screening misinformation. Biometric applications explore innovations in human identification using facial and finger vein recognition, facial micro-expression analysis, and fatigue detection. Advanced applications extend to handwritten recognition, tracking supermarket customer behavior, parcel sorting, predicting road surface conditions, and plastic waste classification. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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US$ 136.74
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Deep Learning for Information Fusion and Pattern Recognition
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US$ 70.85
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Add to basketTaschenbuch. Condition: Neu. Magnesium Alloys as Degradable Biomaterials | Yufeng Zheng | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | CRC Press | EAN 9780367575502 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Image Fusion and Its Applications
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Add to baskethardcover. Condition: Gut. 313 Seiten; 9783527341269.3 Gewicht in Gramm: 1.
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US$ 136.42
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Application of Biomaterials in the Treatment of Cardiovascular Diseases
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Application of Biomaterials in the Treatment of Cardiovascular Diseases
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