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DSAI 2023: 1st International Conference on Data Science & Artificial Intelligence

ACCEPTED PAPERS

  • [Paper#5] Using the New YoLo Models in Detecting Small-sized Objects in the Case of Rice Grains on Branche (Khang Nguyen Quoc, Anh Nguyen Quynh, Hoang Tran Ngoc and Luyl-Da Quach)
  • [Paper#7] Segmentation of NKX2.5 Signal in Human pluripotent Stem Cell-derived Cardiomyocytes (Siem Jongsma, Verena Schwach, Simone A. Ten Den, Robert Passier, Fons J. Verbeek and Lu Cao)
  • [Paper#10] Comparative Evaluation of Classification Models for Reports on Digital Development (Uvini Ranaweera, Bawun Mawitagama, Sanduni Liyanage, Sandupa Keshan, Tiloka De.Silva and Supun Hewawalpita)
  • [Paper#14] SecureQNN: Introducing a Privacy-Preserving Framework for QNNs at the Deep Edge (Miguel Costa, Tiago Gomes, Jorge Cabral, João Monteiro, Adriano Tavares and Sandro Pinto)
  • [Paper#18] Chaotic Mountain Gazelle Optimizer (CMGO): A Robust Optimization Algorithm for K-Means Clustering of Diverse Data Types (Tanatip Watthaisong, Khamron Sunat and Nipotepat Muangkote)
  • [Paper#20] A Case Study to Predict Failure on Secondary School (Sofia Jordão, Dalila Duraes and Paulo Novais)
  • [Paper#21] ChatGPT Knows Your Attacks: Synthesizing Attack Trees Using LLMs (Olga Gadyatskaya and Dalia Papuc)
  • [Paper#24] Deep-Learning-Based LSTM Model for Predicting Tidal River Water Level: A Case Study of the Kapuas Kecil River, Indonesia (Kanada Kurniawan, Joko Sampurno, Riza Adriat, Randy Ardianto and Arie Antasari Kushadiwijayanto)
  • Paper#26] Exploration of the feasibility and applicability of transfer learning in code smell detection (Peeradon Sukkasem and Chitsutha Soomlek)
  • [Paper#28] Data Augmentation for EEG Motor Imagery Classification using Diffusion Model (Nutapol Soingern, Akraradet Sinsamersuk, Itthi Chatnuntawech and Chaklam Silpasuwanchai)
  • [Paper#30] Deep Learning Implementation for Pineapple Maturity and Sweetness Classification (Sayed Muchallil, Rahmad Dawood, Silvia Roza, Yudi Candra, Muhammad Hafez Al-Assad and Maya Fitria)
  • [Paper#36] Implementation of Hybridization : Grey Wolf Optimizer – Dragonfly Algorithm to Improve Model Prediction : Support Vector Classifier – An Experiment (Said Afghani and Khamron Sunat)
  • [Paper#44] Generative Design Optimization for Tourism-Oriented Souvenir Development: Blending Art and Science into Tourism Industry (Somlak Kielarova and Prapasson Pradujphongphet)
  • [Paper#46] WEB USAGE MINING FOR DETERMINING A WEBSITE’S USAGE PATTERN: A Case Study of Government Website (Panunsiya Rawira and Vatcharaporn Esichaikul)
  • [Paper#47] Navigating the Implications of AI in Indonesian Education: Tutors, Governance, and Ethical Perspectives (Daphne Wong-A-Foe)
  • [Paper#49] BERT Fine-tuning the Covid-19 Open Research Dataset for Named Entity Recognition (Shin Thant, Teeradaj Racharak and Frederic Andres)
  • [Paper#50] Improving Low Light Object Detection using Image Enhancement Models (Muhammad Omer Farooq Bhatti and Matthew Dailey)
  • [Paper#53] Thai Conversational Chatbot Classification using BiLSTM and Data Augmentation (Nunthawat Lhasiw, Tanatorn Tanantong and Nuttapong Sanglerdsinlapachai)
  • [Paper#54] A Computer Scientist’s View on Machine Learning and Creativity (Maarten H. Lamers)
  • [Paper#55] Unsupervised Segmentation of High-throughput Zebrafish Images using Deep Neural Networks and Transformers (Shima Javanmardi, Xiaoqin Tang, Mehrdad Jahanbanifard and Fons Verbeek)
  • [Paper#58] DeepFakes Detection using Deep Learning (Mariam Rehman, Mehran Rasool and Sadaf Safdar)
  • [Paper#59] Exploring Deep Learning Techniques for Vision-Based Vehicle Re-Identification: A Traffic Intersection Case Study (Biplav Regmi, Matthew Dailey and Mongkol Ekpanyapong)
  • [Paper#62] Optimizing Heart Disease Classification: Exploring the Impact of Feature Selection and the Performance of Machine Learning Algorithms (Aga Maulana, Farrasa Faisyal, Faris Tarmizi, Taufik Abidin and Hammam Riza)
  • [Paper#66] A Modified Hybrid RBF-BP Network Classifier for Nonlinear Estimation/Classification and Its Applications (Jeff Wong and Po Chai Wong)
  • [Paper#67] Enhancing Data Science Interoperability: An Innovative System for Managing OpenEHR Structures (Miguel Dias, Regina Sousa, Júlio Duarte, Hugo Peixoto, António Abelha and José Machado)
  • [Paper#69] Bayesian Network for Classifying and Predicting Ship shipCollision (Iis Ratih)
  • [Paper#70] A Machine Learning Approach to Evaluating the Relationship between Dental Extraction and Craniofacial Growth in Adolescents (Guillermo Hernandez, Alfonso Gonzalez-Briones, Jose Machado, Pablo Chamoso and Paulo Novais)

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