Image and Video Processing and Recognition Based on Artificial Intelligence (Volume II)

doi:10.3390/books978-3-0365-7603-9

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https://mdpi.com/books/pdfview/book/7341

Contributor(s)

Park, Kang Ryoung (editor)

Lee, Sangyoun (editor)

Kim, Euntai (editor)

Language

English

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Abstract

This reprint focuses on challenging issues in the field of AI-based image and video processing and recognition, including the topics of AI-based image processing, understanding, recognition, compression, and reconstruction; AI-based video processing, understanding, recognition, compression, and reconstruction; computer vision based on AI; AI-based biometrics; AI-based object detection and tracking; approaches that combine AI techniques and conventional methods for image and video processing and recognition; explainable AI (XAI) for image and video processing and recognition; generative adversarial network (GAN)-based image and video processing and recognition; and approaches that combine AI techniques and blockchain methods for image and video processing and recognition.

URI

https://directory.doabooks.org/handle/20.500.12854/100877

Keywords

Finger-vein recognition; motion blur image restoration; modified DeblurGAN; CNN; deep learning; stress recognition; stress database; spatial attention; temporal attention; facial landmark; pose estimation; convolutional neural network; lightweight; knowledge distillation; histogram oriented graphic; multi-camera multi-object tracking; detection quality; traffic sign recognition; sliding windows; meta learning; classification; construction sign detection; image synthesis; cut-and-paste; perspective transformation; group-sparsity loss; temporal attention module; video-based pedestrian-attribute recognition; gait recognition; self-supervised learning; multi-task learning; weakly-supervised learning; biometrics; cross-sensor fingerprints; fingerprint enhancement; cGAN; adversarial learning; video summarization; spatial–temporal features; cross-attention; adaptive video streaming; A-LSTM networks; bit rate measurement; client–server model; HTTP; reference metrics; video quality; image deraining; neural network; vision transformer; generative adversarial network; computer vision; information retrieval; content-based video retrieval; anomaly detection; generation error; feature trajectory smoothness; surveillance video; facial expression recognition; spatial transformation network; attention mechanism; triplet loss function; intra-similarity problem; breast cancer; ultrasonography; autoencoder; brain image registration; generation adversarial network; hand detection; hand classification; YOLO-family networks; convolutional neural networks (CNNs); egocentric vision; unsupervised learning; reinforcement learning; piecewise linear interpolation