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Advances in Image Enhancement

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dual networks; enhanced CNN; fine learning block; image super-resolution; attention mechanism; convolutional neural networks; deep learning; generative adversarial networks; multiple domains; translate images; restart strategy; adaptive adjustment; particle swarm optimization; spline interpolation; image denoising; GAN; optimization algorithm; autoencoder; ResNet; object detection; YOLOv5s; image segmentation; wavelet scattering; loss function; active contour; medical image; image stitching; camera calibration; layered projection; binocular ranging; stereo correction; HOG; feature fusion; DHV recognition; image enhancement; cross stage partial network; zero-reference; Ghost module; NDT registration; map building; RandLa-Net; random sampling; semantic segmentation; capsule network; power line scene recognition; complex background; Visual SLAM; dynamic scene; YOLOv5; K-means clustering; probability update; side-scan sonar; segmentation; CNN; SE-block; multi-channel; blockchain technology; electronic bidding; system design; A-star algorithm; artificial potential field method; least squares method; path planning; night image dehazing; encoder–decoder architecture; image fusion; multi-scale network; serial architecture; U-net; blind watermark removal; low illumination; Retinex theory; histogram equalization; wavelet transform; color moments; non-local mean filter

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