Deep Learning in Image Processing and Pattern Recognition
Materialtyp:
ArtikelUtgivningsinformation: MDPI - Multidisciplinary Digital Publishing Institute 2025Beskrivning: 1 electronic resource (610 p.)Innehållstyp: - text
- computer
- online resource
- 9783725843718
- 9783725843725
- Economics, Finance, Business and Management
- Industry & industrial studies
- Media, entertainment, information and communication industries
- Information technology industries
- BERT
- BLSTM network
- BiGRU
- CNN
- DRSN
- Deep SORT
- DenseNet
- E-ELAN network
- ECA net module
- HDR image
- K-means
- Kinect
- L-BFGS quasi-Newton method
- PSA attention mechanism
- Phosphor in Glass
- ReInForM routing protocol
- Retinex
- Retinex algorithm
- Soft-NMS
- VGG16
- X-ray security image
- XLNET
- YOLOv3-tiny
- YOLOv4
- YOLOv7
- acceptance domain
- action recognition
- adaptive logarithmic transformation
- anomaly detection
- attention
- attention mechanism
- blueprint-separable convolution
- channel attention
- character recognition
- circuit fault diagnosis
- class imbalance
- cognitive radio (CR)
- connected attention
- convolutional autoencoder
- convolutional neural network
- coverage hole
- crowd counting
- data augmentation
- deep convolutional neural networks
- deep learning
- deep learning models
- deformable convolution
- degradation model
- density map estimation
- depthwise over-parameterized convolution
- depthwise separable convolution (DSC)
- detrended fluctuations analysis (DFA)
- differentiable architecture search (DARTS)
- dilated convolution
- dual illumination estimation
- efficien
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This Reprint aims to provide readers with an extensive insight into the latest developments in image processing technology. As images are the main method by which humans acquire and exchange information, the application of image processing is inevitably involved in all aspects of human life. Currently, image processing technology holds a prominent role in the aerospace, public security, biomedicine, industrial engineering, and business communication fields. Recent years have seen the rapid development of image processing, especially with the application of deep learning, enabling it to become the most successfully applied intelligent technology. Pattern recognition is an important research field in image processing and includes image preprocessing, feature extraction and selection, classifier design, and classification decisions. Focusing on these elements, this Reprint covers advancements in thirteen research directions, including image preprocessing, features and selection of images, pattern recognition in image processing technology, image processing in intelligent transportation, hyperspectral image processing, biomedical image processing, image processing in intelligent monitoring, deep learning for image processing, deep learning for image processing.
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eng
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