Computer Vision and Machine Intelligence Paradigms for SDGs Select Proceedings of ICRTAC-CVMIP 2021
by
 
Kannan, R. Jagadeesh. editor.

Title
Computer Vision and Machine Intelligence Paradigms for SDGs Select Proceedings of ICRTAC-CVMIP 2021

Author
Kannan, R. Jagadeesh. editor.

ISBN
9789811971693

Edition
1st ed. 2023.

Physical Description
XVII, 339 p. 162 illus., 131 illus. in color. online resource.

Series
Lecture Notes in Electrical Engineering, 967

Contents
PTZ-camera-based facial expression analysis using faster R-CNN for student engagement recognition -- Convergence Perceptual Model for Computing Time-Series-Data on Fog-Environment -- Localized Super Resolution for Foreground Images using U-Net and MR-CNN -- SMS Spam Classification Using PSO-C4.5 -- Automated Sorting, Grading of Fruits Based on Internal and External Quality Assessment Using HSI, Deep CNN -- Pest Detection using Improvised YOLO Architecture -- Classification of Fungi Effected Psidium Guajava Leaves using ML and DL Techniques -- Deep Learning Based Recognition of Plant Diseases -- Artificial Cognition of Temporal Events using Recurrent Point Process Networks -- On the Performance of Energy Efficient Video Transmission over LEACH based protocol in WSN -- Hybridization of Texture Features for Identification of Bi-lingual Scripts from Camera Images at Wordlevel -- Advanced Algorithmic Techniques for Topic Prediction and Recommendation - An Analysis -- Implementation of an automatic EEG feature extraction with Gated Recurrent Neural Network for Emotion Recognition.

Added Author
Kannan, R. Jagadeesh.
 
Thampi, Sabu M.
 
Wang, Shyh-Hau.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
https://doi.org/10.1007/978-981-19-7169-3


LibraryMaterial TypeItem BarcodeShelf Number[[missing key: search.ChildField.HOLDING]]Status
Online LibraryE-Book520185-1001ONLINEElektronik Kütüphane