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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Xehetasun bibliografikoak
Formatua:	Online
Hizkuntza:	ingelesa
Argitaratua:	MDPI - Multidisciplinary Digital Publishing Institute 2025
Gaiak:	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
Sarrera elektronikoa:	ONIX_20250220_9783725830008_518
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Deep Learning for Information Fusion and Pattern Recognition

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