The Schedule
Day-3 : 8 Sep 2023
8:45 – 10:00 Session-9 Machine Learning-II
Session Chair : Paul Grace
Kanokphon Kane, Khwunta Kirimasthong and Tossapon Boongoen
Available Website Names Classification Using Naïve Baye
Yifan Xiao, Jing Dong, Qiang Zhang, Pengfei Yi, Rui Liu and Xiaopeng Wei
Semi-supervised Semantic Segmentation with Complementary Reconfirmation Mechanism
Dishita Naik and Nitin Naik
An Introduction to Federated Learning: Working, Types, Benefits and Limitations
Dishita Naik and Nitin Naik
The Changing Landscape of Machine Learning: A Comparative Analysis of Centralized Machine Learning, Distributed Machine Learning and Federated Machine Learning
Mohammed Al-Refai, Ahmad Alzu'Bi, Naba Bani Yaseen and Taymaa Obeidat
Arabic Sentiment Analysis with Federated Deep Learning
10:00 – 10:45 Keynote 3 Prof. Durgesh Mishra, SMIEEE
Machine Learning Made Easy: A Case Study on Computer Vision in AWS
Session Chair : Neil Mac Parthaláin
10:45 – 11:00 Tea & Coffee Break
11:00 - 12:30 Session 10 AI Applications-II
Session Chair : Tossapon Boongoen
Alaa Aljamea and Xiaojun Zeng
Predicting the Popularity of YouTube Videos: A Data-Driven Approach
Ishita Naik, Dishita Naik and Nitin Naik
Artificial Intelligence (AI) Applications in Chemistry
Enguerrand Boitel
A Comparative Analysis of GPT-3 and BERT Models for Text-based Emotion Recognition: Performance, Efficiency, and Robustness
Ishita Naik, Dishita Naik and Nitin Naik
Demystifying Working, Types, Benefits and Limitations of Chatbots
Ambrish Srivastav and Shaligram Prajapat
Investigation of Decision Support System for Indian Penal Code Section using Similarity Algorithm and Fuzzy Logic
Shaligram Prajapat, Shraddha Bhurre, Sunny Raikwar and Deepika Pathak
Analyzing and Comparing Clustering Algorithms for Student Academic Data