Deep Learning in Image Processing and Pattern Recognition

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. Current...

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Hōputu:	Online
Reo:	Ingarihi
I whakaputaina:	MDPI - Multidisciplinary Digital Publishing Institute 2025
Ngā marau:	modulation recognition modulation classification support vector machine K-means lightweight network structure hybrid feature pyramid BLSTM network acceptance domain attention mechanism coverage hole hybrid heterogeneous wireless sensor network (WSN) priority mechanism patching image enhancement Retinex algorithm ECA net module connected attention low brightness background scene text image super-resolution multi-task learning scene text recognition transformer furniture image classification deep learning VGG16 group convolution depthwise over-parameterized convolution high dynamic range tone mapping piecewise linear mapping local contrast the least squares method weights HDR image Retinex ensemble empirical pattern decomposition (EEMD) multifractal detrended fluctuations analysis (DFA) support vector machines (SVM) circuit fault diagnosis mathematical morphology fractal dimension kernel principal component analysis variational modal decomposition feature extraction cognitive radio (CR) spectrum prediction long short-term memory network (LSTM) long sequence time-series forecasting (LSTF) signal-dependent noise noise parameter estimation convolutional neural network image denoising fall detection YOLOv7 dual illumination estimation CNN Deep SORT sparse signal reconstruction L-BFGS quasi-Newton method two-loop recursion algorithm reconstruction rate adaptive logarithmic transformation preprocessing ReInForM routing protocol energy selection erasure correcting coding fault-tolerant machine node residual energy ranking intelligent retail anomaly detection graph convolutional networks action recognition semantic segmentation speech emotion recognition mel-spectrogram DRSN BiGRU facial expression recognition (FER) DenseNet depthwise separable convolution (DSC) posture normalization generative adversarial network (GAN) crowd counting density map estimation spatial pyramid pooling (SPP) multi-scale feature extraction dilated convolution X-ray security image YOLOv4 deformable convolution path aggregation network Soft-NMS head position estimation viewpoint tracking unscented Kalman filter Kinect text emotion recognition XLNET attention BERT quality of life walking scene walkability object detection deep convolutional neural networks knowledge distillation gaze estimation algorithm face feature extractor feature information PSA attention mechanism hyperspectral image (HSI) classification neural architecture search differentiable architecture search (DARTS) multi-scale attention mechanism data augmentation class imbalance YOLOv3-tiny convolutional autoencoder smoke detection image quality enhancement deep learning models level set models Phosphor in Glass industrial detection degradation model scene text image super resolution single-image super-resolution blueprint-separable convolution efficient transformer spatial attention channel attention electronic speckle pattern interferometry (ESPI) phase extraction fringe pattern wrapped phase maps small target detection E-ELAN network human pose estimation character recognition neural network n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
Urunga tuihono:	ONIX_20250812T110751_9783725843718_456
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ONIX_20250812T110751_9783725843718_456

Deep Learning in Image Processing and Pattern Recognition

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