Image and Video Processing and Recognition Based on Artificial Intelligence
This book includes 23 published papers on Special issues of "Image and Video Processing and Recognition Based on Artificial Intelligence" in the journal Sensors. The purpose of this Special Issue was to invite high-quality and state-of-the-art academic papers on challenging issues in the f...
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| Format: | Book Chapter |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Online Access: | Get Fullteks DOAB: description of the publication |
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| LEADER | 05552naaaa2201633uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_76850 | ||
| 005 | 20220111 | ||
| 020 | |a books978-3-0365-1591-5 | ||
| 020 | |a 9783036515922 | ||
| 020 | |a 9783036515915 | ||
| 024 | 7 | |a 10.3390/books978-3-0365-1591-5 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 072 | 7 | |a TB |2 bicssc | |
| 100 | 1 | |a Park, Kang Ryoung |4 edt | |
| 700 | 1 | |a Lee, Sangyoun |4 edt | |
| 700 | 1 | |a Kim, Euntai |4 edt | |
| 700 | 1 | |a Park, Kang Ryoung |4 oth | |
| 700 | 1 | |a Lee, Sangyoun |4 oth | |
| 700 | 1 | |a Kim, Euntai |4 oth | |
| 245 | 1 | 0 | |a Image and Video Processing and Recognition Based on Artificial Intelligence |
| 260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
| 300 | |a 1 electronic resource (431 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a This book includes 23 published papers on Special issues of "Image and Video Processing and Recognition Based on Artificial Intelligence" in the journal Sensors. The purpose of this Special Issue was to invite high-quality and state-of-the-art academic papers on challenging issues in the field of AI-based image and video processing and recognition. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Technology: general issues |2 bicssc | |
| 653 | |a emotion recognition | ||
| 653 | |a brain computer interface | ||
| 653 | |a bag of deep features | ||
| 653 | |a continuous wavelet transform | ||
| 653 | |a face image analysis | ||
| 653 | |a deep learning | ||
| 653 | |a face parsing | ||
| 653 | |a facial attributes classification | ||
| 653 | |a building extraction | ||
| 653 | |a convolutional neural networks | ||
| 653 | |a mask R-CNN | ||
| 653 | |a high-resolution remote sensing image | ||
| 653 | |a autoencoders | ||
| 653 | |a semi-supervised learning | ||
| 653 | |a computer vision | ||
| 653 | |a pathology | ||
| 653 | |a epidermis | ||
| 653 | |a skin | ||
| 653 | |a image processing | ||
| 653 | |a generative models | ||
| 653 | |a generative adversarial net | ||
| 653 | |a depth map | ||
| 653 | |a super-resolution | ||
| 653 | |a guidance | ||
| 653 | |a residual network | ||
| 653 | |a channel interaction | ||
| 653 | |a pose estimation | ||
| 653 | |a body orientation | ||
| 653 | |a multi-person | ||
| 653 | |a multi-task | ||
| 653 | |a surface defect detection | ||
| 653 | |a active learning | ||
| 653 | |a generative adversarial network | ||
| 653 | |a presentation attack detection | ||
| 653 | |a artificial image generation | ||
| 653 | |a presentation attack face images | ||
| 653 | |a ultrasound image | ||
| 653 | |a malignant thyroid nodule | ||
| 653 | |a artificial intelligence | ||
| 653 | |a weighted binary cross-entropy loss | ||
| 653 | |a infrared circumferential scanning system | ||
| 653 | |a target recognition | ||
| 653 | |a deep convolutional neural networks | ||
| 653 | |a data augmentation | ||
| 653 | |a transfer learning | ||
| 653 | |a bounding box regression | ||
| 653 | |a loss function | ||
| 653 | |a medical image fusion | ||
| 653 | |a convolutional neural network | ||
| 653 | |a image pyramid | ||
| 653 | |a multi-scale decomposition | ||
| 653 | |a armature | ||
| 653 | |a surface inspection | ||
| 653 | |a action recognition | ||
| 653 | |a social robotics | ||
| 653 | |a common spatial patterns | ||
| 653 | |a vehicle recognition | ||
| 653 | |a multi resolution network | ||
| 653 | |a optimization | ||
| 653 | |a semantic segmentation | ||
| 653 | |a global context | ||
| 653 | |a local context | ||
| 653 | |a fully convolutional networks | ||
| 653 | |a image-to-image conversion | ||
| 653 | |a image de-raining | ||
| 653 | |a label to photos | ||
| 653 | |a edges to photos | ||
| 653 | |a generative adversarial network (GAN) | ||
| 653 | |a remote sensing | ||
| 653 | |a helicopter footage | ||
| 653 | |a crowd counting | ||
| 653 | |a multitask learning | ||
| 653 | |a normalized cross-correlation | ||
| 653 | |a Marr wavelets | ||
| 653 | |a entropy and response | ||
| 653 | |a graph matching | ||
| 653 | |a RANSAC | ||
| 653 | |a GC-LSTM model | ||
| 653 | |a typhoon | ||
| 653 | |a satellite image | ||
| 653 | |a prediction system | ||
| 653 | |a monocular depth estimation | ||
| 653 | |a feature distillation | ||
| 653 | |a joint attention | ||
| 653 | |a finger-vein recognition | ||
| 653 | |a camera position | ||
| 653 | |a finger position | ||
| 653 | |a lighting | ||
| 653 | |a unobserved database | ||
| 653 | |a heterogeneous database | ||
| 653 | |a domain adaptation | ||
| 653 | |a cycle-consistent adversarial networks | ||
| 653 | |a SDUMLA-HMT-DB | ||
| 653 | |a HKPolyU-DB | ||
| 653 | |a biometrics | ||
| 653 | |a face recognition | ||
| 653 | |a single-sample face recognition | ||
| 653 | |a binarized statistical image features | ||
| 653 | |a K-nearest neighbors | ||
| 653 | |a sparse coding | ||
| 653 | |a fast approximation | ||
| 653 | |a homotopy iterative hard thresholding | ||
| 653 | |a object recognition | ||
| 653 | |a character recognition | ||
| 653 | |a orthogonal polynomials | ||
| 653 | |a orthogonal moments | ||
| 653 | |a Krawtchouk polynomials | ||
| 653 | |a Tchebichef polynomials | ||
| 653 | |a support vector machine | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/4300 |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/76850 |7 0 |z DOAB: description of the publication |