Items where Author is "Thailambal, G."

Article

Sudharsan, M. and Thailambal, G. (2023) Alzheimer's disease prediction using machine learning techniques and principal component analysis (PCA). Materials Today: Proceedings, 81. pp. 182-190. ISSN 22147853

Yogeshwari, M. and Thailambal, G. (2023) Automatic feature extraction and detection of plant leaf disease using GLCM features and convolutional neural networks. Materials Today: Proceedings, 81. pp. 530-536. ISSN 22147853

Kiruthika, N.S. and Thailambal, G. (2022) Light weight recommendation system for social networking analysis using a hybrid BERT-SVM classifier algorithm. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 22 (4). pp. 769-778. ISSN 22261494

Thailambal, G. and Ananthi, Sheshasaayee (2019) A Different Text Mining Process for Classifying Journal Databases using Machine Learning Algorithms. International Journal of Recent Technology and Engineering, 8 (2S11). pp. 239-243. ISSN 2277-3878

Book Section

Meenakshi, G. and Thailambal, G. (2021) A Contemporary Method on Feature Selection and Classification Using Multi-Model Deep Learning Technique for Identifying Diabetic Retinopathy. In: Advances in Parallel Computing Technologies and Applications. IOS Press.

Conference or Workshop Item

Meenakshi, J. and Thailambal, G. (2023) Gender and Age Detection Techniques for Blind People using Principal Component Analysis. In: 2023 International Conference on Inventive Computation Technologies (ICICT), Lalitpur, Nepal.

Nandhini, K. and Thailambal, G. (2022) CNN-OSBO Encoder-Decoder Architecture for Drug-Target Interaction (DTI) Prediction of Covid-19 Targets. In: 2022 6th International Conference on Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India.

Sudharsan, M. and Thailambal, G. (2022) An Recognition of Alzheimer Disease using Brain MRI Images with DPNMM through Adaptive Model. In: 2022 International Conference on Edge Computing and Applications (ICECAA), Tamilnadu, India.

Sudharsan, M. and Thailambal, G. (2022) Alzheimer’s disease: Early-Stage Prediction and Classification using Multi-Model Technique. In: 2022 International Conference on Inventive Computation Technologies (ICICT), Nepal.

Meenakshi, G. and Thailambal, G. (2022) Categorisation and Prognosticationof Diabetic Retinopathy using Ensemble Learning and CNN. In: 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India.

Sudharsan, M. and Thailambal, G. (2022) A Hybrid Learning Approach for Early-Stage Prediction and Classification of Alzheimer's Disease Using Multi-Features. In: 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India.

Kalaiselvi, S. and Thailambal, G. (2022) A comparative analysis of multiple methodologies of brain tumor detection in machine learning techniques. In: THE FIRST INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTATIONAL SCIENCE AND ENGINEERING: ICACSE 2020, 25–26 December 2020, Coimbatore, India.

Sudharsan, M. and Thailambal, G. (2022) A meta-analysis and roadmap of Alzheimer’s diseases prediction by machine learning algorithms. In: INDUSTRIAL, MECHANICAL AND ELECTRICAL ENGINEERING, 7 March 2019, Brunei.

Meenakshi, G. and Thailambal, G. (2021) A Study on Various Classifications and Prediction Techniques for Diabetic Retinopathy. In: 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India.