Deep Learning for Information Fusion and Pattern Recognition
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 fi...
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| Γλώσσα: | Αγγλικά |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Διαθέσιμο Online: | ONIX_20250220_9783725830008_518 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-153154 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1531542025-02-20T13:38:48Z Deep Learning for Information Fusion and Pattern Recognition Zheng, Yufeng Blasch, Erik CNN dual-channel biometric identification system biometric fusion face recognition finger vein recognition identification system deeper learning multiple information fusion YOLOv4 express sorting information to identify plastic bottles recycling hyperspectral image multi-scale feature fusion deep learning semantic segmentation image segmentation transformer convolutional neural networks multiple annotators chained approach generalized cross-entropy classification dense video caption video captioning multi-modal feature fusion feature extraction neural network facial micro-expression human-machine interaction long short-term memory (LSTM) convolutional neural network (CNN) vision transformer score fusion child handwriting handwritten character recognition writer-group classification convolutional neural network machine learning fake news ensemble of classifiers text classification misinformation multiframe super-resolution fusion of interpolated frames image restoration subpixel registration smart shelves visual analytics retail analytics computer vision sensor fusion intelligent traffic fatigue detection heart rate bidirectional LSTM RGB-D salient object detection multi-modal and multi-scale features multimodal analysis time-series processing winter road surface condition thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science 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. 2025-02-20T13:38:45Z 2025-02-20T13:38:45Z 2025 book ONIX_20250220_9783725830008_518 9783725830008 9783725829996 https://directory.doabooks.org/handle/20.500.12854/153154 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/10446 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2999-6 10.3390/books978-3-7258-2999-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725830008 9783725829996 256 Basel open access |
| spellingShingle | CNN dual-channel biometric identification system biometric fusion face recognition finger vein recognition identification system deeper learning multiple information fusion YOLOv4 express sorting information to identify plastic bottles recycling hyperspectral image multi-scale feature fusion deep learning semantic segmentation image segmentation transformer convolutional neural networks multiple annotators chained approach generalized cross-entropy classification dense video caption video captioning multi-modal feature fusion feature extraction neural network facial micro-expression human-machine interaction long short-term memory (LSTM) convolutional neural network (CNN) vision transformer score fusion child handwriting handwritten character recognition writer-group classification convolutional neural network machine learning fake news ensemble of classifiers text classification misinformation multiframe super-resolution fusion of interpolated frames image restoration subpixel registration smart shelves visual analytics retail analytics computer vision sensor fusion intelligent traffic fatigue detection heart rate bidirectional LSTM RGB-D salient object detection multi-modal and multi-scale features multimodal analysis time-series processing winter road surface condition thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science Deep Learning for Information Fusion and Pattern Recognition |
| title | Deep Learning for Information Fusion and Pattern Recognition |
| title_full | Deep Learning for Information Fusion and Pattern Recognition |
| title_fullStr | Deep Learning for Information Fusion and Pattern Recognition |
| title_full_unstemmed | Deep Learning for Information Fusion and Pattern Recognition |
| title_short | Deep Learning for Information Fusion and Pattern Recognition |
| title_sort | deep learning for information fusion and pattern recognition |
| topic | CNN dual-channel biometric identification system biometric fusion face recognition finger vein recognition identification system deeper learning multiple information fusion YOLOv4 express sorting information to identify plastic bottles recycling hyperspectral image multi-scale feature fusion deep learning semantic segmentation image segmentation transformer convolutional neural networks multiple annotators chained approach generalized cross-entropy classification dense video caption video captioning multi-modal feature fusion feature extraction neural network facial micro-expression human-machine interaction long short-term memory (LSTM) convolutional neural network (CNN) vision transformer score fusion child handwriting handwritten character recognition writer-group classification convolutional neural network machine learning fake news ensemble of classifiers text classification misinformation multiframe super-resolution fusion of interpolated frames image restoration subpixel registration smart shelves visual analytics retail analytics computer vision sensor fusion intelligent traffic fatigue detection heart rate bidirectional LSTM RGB-D salient object detection multi-modal and multi-scale features multimodal analysis time-series processing winter road surface condition thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science |
| topic_facet | CNN dual-channel biometric identification system biometric fusion face recognition finger vein recognition identification system deeper learning multiple information fusion YOLOv4 express sorting information to identify plastic bottles recycling hyperspectral image multi-scale feature fusion deep learning semantic segmentation image segmentation transformer convolutional neural networks multiple annotators chained approach generalized cross-entropy classification dense video caption video captioning multi-modal feature fusion feature extraction neural network facial micro-expression human-machine interaction long short-term memory (LSTM) convolutional neural network (CNN) vision transformer score fusion child handwriting handwritten character recognition writer-group classification convolutional neural network machine learning fake news ensemble of classifiers text classification misinformation multiframe super-resolution fusion of interpolated frames image restoration subpixel registration smart shelves visual analytics retail analytics computer vision sensor fusion intelligent traffic fatigue detection heart rate bidirectional LSTM RGB-D salient object detection multi-modal and multi-scale features multimodal analysis time-series processing winter road surface condition thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology thema EDItEUR::P Mathematics and Science |
| url | ONIX_20250220_9783725830008_518 |