Intelligent Spot Detection for Degraded Image Sequences Based on Machine Vision-Reference-Cited by-同舟云学术

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Intelligent Spot Detection for Degraded Image Sequences Based on Machine Vision

Published:2022-04-13 Issue:6 Volume:27 Page:2429-2436
ISSN:1383-469X
Container-title:Mobile Networks and Applications
language:en
Short-container-title:Mobile Netw Appl

Author:

Tian Qiao,Wang Sen^ORCID,Pan Lei

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s11036-021-01888-1.pdf

Reference26 articles.

1. Sangaiah AK, Samuel OW, Li X, Abdel-Basset M, Wang H (2018) Towards an efficient risk assessment in software projects–Fuzzy reinforcement paradigm. Comput Electr Eng 71:833–846

2. Zhao Y, Jiang H, Chen Q, Qin Y, Xie H, Wu Y, Liu S, Zhou Z, Xia J, Zhou F (2021) Preserving Minority Structures in Graph Sampling. IEEE Trans Vis Comput Graph 27(2):1–10

3. Lin Y, Tu Y, Dou Z et al (2021) Contour stella image and deep learning for signal recognition in the physical layer. IEEE Trans Cogn Commun Netw 7(1):34–46

4. Kumaran N, Reddy US (2020) Classification of human activity detection based on an intelligent regression model in video sequences. IET Image Process 1–12

5. Wei W, Song H, Li W, Shen P, Vasilakos A (2017) Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network. Inf Sci 408(2):100–114

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