Open Science Research Excellence

ICAINN 2021 : International Conference on Artificial Intelligence and Neural Networks

London, United Kingdom
June 28 - 29, 2021

Conference Code: 21UK06ICAINN

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

ICAINN 2021 has teamed up with the Special Journal Issue on Artificial Intelligence and Neural Networks. 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   May 13, 2021
Notification of Acceptance/Rejection   May 31, 2021
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   May 27, 2021
Conference Dates   June 28 - 29, 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) Thresholding Approach for Automatic Detection of Pseudomonas aeruginosa Biofilms from Fluorescence in situ Hybridization Images
Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj
3) Deep Learning Based 6D Pose Estimation for Bin-Picking Using 3D Point Clouds
Hesheng Wang, Haoyu Wang, Chungang Zhuang
4) Comparing Machine Learning Estimation of Fuel Consumption of Heavy-Duty Vehicles
Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi
5) Image Ranking to Assist Object Labeling for Training Detection Models
Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman
6) Model of Optimal Centroids Approach for Multivariate Data Classification
Pham Van Nha, Le Cam Binh
7) Performance Prediction Methodology of Slow Aging Assets
M. Ben Slimene, M.-S. Ouali
8) Neural Network Models for Actual Cost and Actual Duration Estimation in Construction Projects: Findings from Greece
Panagiotis Karadimos, Leonidas Anthopoulos
9) Predicting the Success of Bank Telemarketing Using Artificial Neural Network
Mokrane Selma
10) Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine
Hira Lal Gope, Hidekazu Fukai
11) Machine Learning Techniques in Bank Credit Analysis
Fernanda M. Assef, Maria Teresinha A. Steiner
12) Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach
V. Veeraprathap, G. S. Harish, G. Narendra Kumar
13) Classifying Turbomachinery Blade Mode Shapes Using Artificial Neural Networks
Ismail Abubakar, Hamid Mehrabi, Reg Morton
14) Convergence Analysis of Training Two-Hidden-Layer Partially Over-Parameterized ReLU Networks via Gradient Descent
Zhifeng Kong
15) Discussing Embedded versus Central Machine Learning in Wireless Sensor Networks
Anne-Lena Kampen, Øivind Kure

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