About Me
Yvon Apedo is a Ph.D. student at Université Paris-Saclay in France, conducting his research in collaboration with the CEA and IBISC laboratories. He is a Demythif.AI Fellow under the Institut DATAIA, co-funded by the Marie Skłodowska-Curie Actions (MSCA) and the European Union. His research focuses on developing efficient multimodal vision transformers for semantic segmentation in autonomous systems. He got a Master’s degree from the School of Computer Science at Northwestern Polytechnical University, Xi’an, China, specializing in deep learning and computer vision. His research focuses on semantic segmentation, object detection, and image classification. Currently, he is conducting his research in the Multimedia Information Processing Team (MIPLab) under the supervision of Professor Tao Huanjie. His MSc thesis, "Crack Segmentation Using Deep Learning," explores 3 contents including fully supervised segmentation with Sift-Semantic Transformer, a weakly supervised learning with adversarial learning, and unsupervised domain adaptation. He holds a BSc (Eng) from Yunnan Technology and Business University, China, under the guidance of Professor Zhu Xiaojing, and an Advanced Diploma in Database Technology from IPMC-Ghana. Previously, He worked as a Senior Professional Designer at Fairpointers in Ghana. His academic and professional journey reflects his passion for solving real-world challenges and developing innovative solutions using artificial intelligence and deep learning techniques.
Research Interests
Deep Learning
Neural networks, transfer learning, and model optimization
Computer Vision
Image processing, object detection, and scene understanding
Data Visualization
Interactive visualizations, data storytelling, and visual analytics
Machine Learning
Predictive modeling, classification, and regression analysis
Publications
Recent Publications
- Weakly Supervised Crack Segmentation Using Adversarial Learning and Transformers Journal of Multimedia Systems(published)
- Unsupervised Domain Adaptation for Crack Segmentation Based on Cross-Domain Stylization and Dual Adversarial Feature Learning Journal of Computing for Civil Engineering(Accepted)
- ADB-Crack: A Transformer-Based Framework with Adaptive Context Fusion and Dynamic Feature Refinement for High-Precision Pavement Crack Segmentation Journal of Automation in Construction (Under Review)
- Systematic Literature Review on Forecasting and Prediction of Technical Debt Evolution —
Software Projects
Amazon Clone
Replica of the Amazon homepage, complete with login and secure checkout system.
Project Peter
Android application featuring user registration and picture publication capabilities.
Vehicles Sales - KOMI (iOS App)
iOS application for vehicle sales, including user registration, vehicle publication, and booking functionalities.
Certifications & Licenses
Learning AI Through Visualization
Columbia University
2025
This course offers a comprehensive introduction to Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), with a focus on practical applications. Through a series of structured modules, learners will explore foundational concepts, from understanding datasets to implementing AI models.
Taught by Ali Hirsa on Columbia +
View CertificateGoogle Advanced Data Analytics Specialization
2025
Contents: Foundations of Data Science, Get Started with Python, Go Beyond the Numbers: Translate Data into Insights, The Power of Statistics, Regression Analysis: Simplify Complex Data Relationships, The Nuts and Bolts of Machine Learning
Taught by GOOGLE on Coursera
View CertificateMachine Learning Specialization
Stanford University and DeepLearning.AI
2023
Contents: Supervised Learning, Unsupervised Learning, Recommender Systems, and Reinforcement Learning
Taught by Andrew Ng on Coursera
View CertificateDeep Learning Specialization
DeepLearning.AI
2023
Contents: Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers
Taught by Andrew Ng on Coursera
View Certificate