BDET 2021 | Virtual Conference | June 25-27, 2021

BDET 2021 was held as an online conference during June 25-27, 2021. BDET 2021 papers will be published in the International Conference Proceedings Series by ACM ( ISBN: 978-1-4503-8928-0 ). All papers will be archived in the ACM Digital Library, and indexed by Ei Compendex and Scopus and submitted to be reviewed by Thomson Reuters Conference Proceedings Citation Index (ISI Web of Science).

 

Keynote Speakers

On June 26-27, Conference Chairs Prof. Liyanage C De Silva opened the conference, Prof. Tang Long Ching chaired the keynote session. Keynote speakers Prof. Yi-Bing Lin, from National Yang Ming Chiao Tung University (YMCU), Taiwan, China;  Prof. Vesna Zeljkovic, from Lincoln University, USA delivered the speech.

 

Opening Speech-Conference Chair:

Prof. Liyanage C De Silva 
Universiti Brunei Darussalam

Keynote Session Host: Conference Chair:

Prof. TANG Loon Ching
National University of Singapore, Singapore

 

 
Prof. Yi-Bing Lin
National Yang Ming Chiao Tung University (YMCU), Taiwan, China

Speech Title:
AgriTalk: A Smart Soil Cultivation Using IoT, Big Data and AI

Prof. Vesna Zeljkovic
Lincoln University, USA

Speech title :
Big Data Deprivation in Selected Medical Imaging


Best Presentation & Session Photos

Presenter: Tianhong Chen
Beijing Institute of Technology, China

Tensor-patch-based Discriminative Marginalized Least Squares Regression for Membranous Nephropathy Hyperspectral Data
Session 3: Computer Science and Data Analysis

Presenter: Jessie Balbin
Mapua University, Philippines

Mobile Geo-tagging and Cloud-based Underwater Garbage Identification using Convolutional Neural Network

Session 4: Big Data and Data Engineering
 

Presenter: Ming-Yen Lin
Feng Chia University, Taiwan

Using Spark for Text Mining on Large Scale Liver Cancer Literature

Session 3: Computer Science and Data Analysis

Presenter: Vignesh Srinivasan
National Institute of Technology Karnataka, India

Data Aggregation of Tweets and Topic Modelling Based on the Twitter Dataset

Session 4: Big Data and Data Engineering

   
   
   

   



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