Open Science Research Excellence

ICAICS 2021 : International Conference on Advances in Intelligent Computing Systems

Singapore, SG
March 29 - 30, 2021

Conference Code: 21SG03ICAICS

Conference Proceedings

All submitted conference papers will be blind peer reviewed by three competent reviewers. The peer-reviewed conference proceedings are indexed in the Open Science Index, Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, and other index databases. Impact Factor Indicators.

Special Journal Issues

ICAICS 2021 has teamed up with the Special Journal Issue on Advances in Intelligent Computing Systems. A number of selected high-impact full text papers will also be considered for the special journal issues. All submitted papers will have the opportunity to be considered for this Special Journal Issue. The paper selection will be carried out during the peer review process as well as at the conference presentation stage. Submitted papers must not be under consideration by any other journal or publication. The final decision for paper selection will be made based on peer review reports by the Guest Editors and the Editor-in-Chief jointly. Selected full-text papers will be published online free of charge.

Conference Sponsor and Exhibitor Opportunities

The Conference offers the opportunity to become a conference sponsor or exhibitor. To participate as a sponsor or exhibitor, please download and complete the Conference Sponsorship Request Form.

Important Dates

Abstracts/Full-Text Paper Submission Deadline   February 15, 2021
Notification of Acceptance/Rejection   March 1, 2021
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   February 28, 2021
Conference Dates   March 29 - 30, 2021

Important Notes

Please ensure your submission meets the conference's strict guidelines for accepting scholarly papers. Downloadable versions of the check list for Full-Text Papers and Abstract Papers.

Please refer to the Paper Submission GUIDE before submitting your paper.

Selected Conference Papers

1) Improved Rare Species Identification Using Focal Loss Based Deep Learning Models
Chad Goldsworthy, B. Rajeswari Matam
2) Building an Integrated Relational Database from Swiss Nutrition National Survey and Swiss Health Datasets for Data Mining Purposes
Ilona Mewes, Helena Jenzer, Farshideh Einsele
3) Deep Learning Based 6D Pose Estimation for Bin-Picking Using 3D Point Clouds
Hesheng Wang, Haoyu Wang, Chungang Zhuang
4) Facial Emotion Recognition with Convolutional Neural Network Based Architecture
Koray U. Erbas
5) Integration of Educational Data Mining Models to a Web-Based Support System for Predicting High School Student Performance
Sokkhey Phauk, Takeo Okazaki
6) Bayesian Deep Learning Algorithms for Classifying COVID-19 Images
I. Oloyede
7) Comparing Machine Learning Estimation of Fuel Consumption of Heavy-Duty Vehicles
Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi
8) A Context-Centric Chatbot for Cryptocurrency Using the Bidirectional Encoder Representations from Transformers Neural Networks
Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li
9) Variational Explanation Generator: Generating Explanation for Natural Language Inference Using Variational Auto-Encoder
Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen
10) Image Ranking to Assist Object Labeling for Training Detection Models
Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman
11) Malaria Parasite Detection Using Deep Learning Methods
Kaustubh Chakradeo, Michael Delves, Sofya Titarenko
12) Real-Time Episodic Memory Construction for Optimal Action Selection in Cognitive Robotics
Deon de Jager, Yahya Zweiri, Dimitrios Makris
13) Author Profiling: Prediction of Learners’ Gender on a MOOC Platform Based on Learners’ Comments
Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea
14) A Hybrid Feature Selection and Deep Learning Algorithm for Cancer Disease Classification
Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh
15) Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine
Hira Lal Gope, Hidekazu Fukai

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