
Computer Vision and Data Science for Engineering Applications
Guest editors: Dr. B. Santhi and Dr. G. R. Brindha · CVDS-19All its articles are published.Articles in this special issue
Each accepted article is published in the journal’s next regular issue as soon as its author approves the proof, and appears here.
- Future Emoji Entry Prediction Using Neural NetworksHelen Wilfred Raj, Santhi Balachandranpp. 150–157 · published 10 Aug 2019View PDF9,137 accesses
- Farmer-Friendly Mobile Application for Automated Leaf Disease Detection of Real-Time Augmented Data Set using Convolution Neural NetworksRishiikeshwer B. S., T. Aswin Shriram, J. Sanjay Raju et al.pp. 158–166 · published 24 Aug 2019View PDF8,987 accesses
- A Descriptive Analysis of Students Learning Skills Using Bloom’s Revised TaxonomyJoy Christy Antony Sami, Umamakeswari Arumugampp. 183–193 · published 4 Sep 2019View PDF8,539 accesses
- A Survey of Data Anonymization Techniques for Privacy-Preserving Mining in BigdataHelen Wilfred Raj, Santhi Balachandranpp. 194–201 · published 31 Dec 2019View PDF8,060 accesses
- An Optimized Mobile Cloud Computational Offloading Framework using K-Means AlgorithmMeena Veeraiyan, S. Kousika, J. Senthilkumar, Joy Christy Antonysamipp. 202–210 · published 31 Jan 2020View PDF8,084 accesses
- Missing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.pp. 211–216 · published 20 Feb 2020View PDF8,114 accesses
- Diabetic Retinopathy Detection using Deep Learning TechniquesAswin Shriram Thiagarajan, Jithendran Adikesavan, Santhi Balachandran, Brindha Ganapathyagraharam Ramamoorthypp. 305–313 · published 13 Mar 2020View PDF10,272 accesses
- Survey on Applications of Electronic NoseS. Keerthana, B. Santhipp. 314–320 · published 15 Mar 2020View PDF8,173 accesses
- Study and Analysis of Prediction Model for Heart Disease Data Using Machine Learning TechniquesB. Santhi, K. Renukapp. 344–354 · published 26 Mar 2020View PDF7,784 accesses
- IoT Framework for Smart Irrigation using Machine Learning TechniqueS. Ramya, A.M. Swetha, Manivannan Doraipandianpp. 355–363 · published 26 Mar 2020View PDF9,654 accesses
- A VF-IMF Cohesion Metric for Object-Oriented ClassesJoy Christy Antony Sami, Umamakeswari Arumugampp. 422–429 · published 10 Apr 2020View PDF8,246 accesses
- Live Migration of Virtual Machines using Mirroring TechniqueEzhilarasie Rajapackiyam, Arvind Venkatesa Subramanian, Umamakeswari Arumugampp. 543–550 · published 31 Mar 2020View PDF8,248 accesses
- Fault Node Detection and Connectivity Restoration with Mobile Relay Node in Wireless Sensor NetworksM.P. Anuradha, A.M. Swetha, Manivannan Doraipandianpp. 551–558 · published 1 Apr 2020View PDF7,917 accesses
- Detection of Pulmonary Nodules in ct Images Using Deep Learning TechniqueSanthi Balachandran, Divya, Nithya Rajendran, Brindha Giripp. 568–575 · published 15 Apr 2020View PDF7,816 accesses
- Irrigation System Using Hyperspectral Data and Machnie Learning Techniques for Smart AgricultureSanthi Balachandran, Sourna Lakshmi, Nithya Rajendranpp. 576–582 · published 15 Apr 2020View PDF7,683 accesses
- Improving Arabic Instant Machine Translation: The Case of Arabic Triangle of LanguageTala M. Albashir, Hussien Alzoubi, Mohammad Albatainihpp. 956–965 · published 20 Jul 2020View PDF7,507 accesses
- Data Streams Curation for Better Machine Learning Functionality and Result to Serve IoT and other Applications: A SurveyHaya Salah, Islam Al-Omari, Jaber Alwidian et al.pp. 1572–1584 · published 1 Nov 2019View PDF8,722 accesses
The call for papers
Read the original call: description and topics
Machine learning (ML) and Deep Learning (DP) are having significant impact in the research area. As the need for real time automatic learning increases, the methods are being finetuned and the research is growing vastly. The applications range from Finance to Webpage, Networking to Biological Analysis and Marketing to IoT. Self learning and automating the processes are the strength of the ML and DP. The analytical learning model offer constant learning by adaptive techniques for the given data. The objective of ML and DP is to generate reliable information that can be executed with less human intervention.
The generalization concept of ML includes successful real time applications such as sales data analysis, prediction of customer behaviour, Spam identification, credit card fraud detection, optimizing robot navigation, extraction of information from biomedical samples, Image, video, signal processing and the list goes on long which includes almost all domains.
The main scope of this special issue is data reasoning and inference, ML and DP techniques to employ self learning and automate engineering applications. In turn this special issue focus to encourage discussion and analysis of research and learning activities in the models and design of engineering applications such as Image processing, Sensor based learning, Biomedical analysis, electrical, mechanical and civil. We specially promote innovative and enhanced ML & DP techniques to tackle the real time applications which are complex in both data & process.
Important dates
- Call opens5 Apr 2019 · done
- Submission deadline15 Jan 2020 · done
- Collection complete15 Apr 2020 · done
Guest editors
- Dr. B. Santhi · lead guest editorAssociate Dean, SASTRA Deemed University, India
- Dr. G. R. BrindhaAssociate Professor, SASTRA Deemed University, India