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Computational vision and bio-inspire...

(1998 :)

Computational vision and bio-inspired computingICCVBIC 2020 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational vision and bio-inspired computingedited by S. Smys ... [et al.].
其他題名:	ICCVBIC 2020 /
其他作者:	Smys, S.
團體作者:
出版者:	Singapore :Springer Singapore :2021.
面頁冊數:	xx, 871 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Computer vision
電子資源:	https://doi.org/10.1007/978-981-33-6862-0
ISBN:	9789813368620$q(electronic bk.)

Computational vision and bio-inspired computingICCVBIC 2020 /
Computational vision and bio-inspired computingICCVBIC 2020 /[electronic resource] :edited by S. Smys ... [et al.]. - Singapore :Springer Singapore :2021. - xx, 871 p. :ill., digital ;24 cm. - Advances in intelligent systems and computing,v.13182194-5357 ;. - Advances in intelligent systems and computing ;176..

Chapter 1. Smart Surveillance Syst+D2:F64em by Face Recognition and Tracking using Machine Learning Techniques -- Chapter 2. Object-based Neural Model in Multicore Environments with Improved Biological Plausibility -- Chapter 3. Advancement in Classification of X Ray Images Using Radial basis Function with Support of Canny Edge Detection Model -- Chapter 4. Brain Tumour Three Class Classification on MRI Scans using Transfer Learning and Data Augmentation -- Chapter 5. Assessing the Statistical Significance of Pairwise Gapped Global Sequence Alignment of DNA Nucleotides using Monte-Carlo Techniques -- Chapter 6. Principal Intregant Analysis Based Liver Disease Prediction using Machine Learning -- Chapter 7. Classification of Indian Classical Dance 3D Point Cloud Data using Geometric Deep Learning -- Chapter 8. Fire Detection by Parallel Classification of Fire and Smoke using Convolutional Neural Network -- Chapter 9. Iris Image Denoising in Spatial Domain: An Implementation based on Modified Median Filtering Approach -- Chapter 10. A Split Key Unique Sudoku Steganography (SKUSS) Based Reversible High Embedded Data Hiding Technique -- Chapter 11. Identification of Insomnia based on Discrete Wavelet Transform using Time domain and Non-Linear features -- Chapter 12. Transfer Learning Techniques for Skin Cancer Classification -- Chapter 13. Particle Swarm Optimization Based on Random Walk -- Chapter 14. Signal processing Algorithms based on Evolutionary Optimization Techniques in the BCI: A Review -- Chapter 15. Cancelation of 50Hz and 60Hz Power-line Interference from Electrocardiogram using Square-root Cubature Kalman Filter.

This book includes selected papers from the 4th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2020), held in Coimbatore, India, from November 19 to 20, 2020. This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human-computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

ISBN: 9789813368620$q(electronic bk.)

Standard No.: 10.1007/978-981-33-6862-0doiSubjects--Topical Terms:

253837
Computer vision

LC Class. No.: TA1634

Dewey Class. No.: 006.37

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520 $a This book includes selected papers from the 4th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2020), held in Coimbatore, India, from November 19 to 20, 2020. This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human-computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.
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