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Anastasios (Tasos) Stamoulakatos
About me
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Posts
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cv
CV
Here you can find my up-to-date curriculum vitae.
ml_projects
Improving the Safety, Reliability, and Efficiency of Cargo Transportation using Deep Learning
Published:
- Multi-class object detection using RetinaNet
- Progress meetings with the industrial partner Streamba
Automatic Identification of Asbestos Fibres in Air Samples using Deep Learning
Published:
- Instance segmentation using U-Net
- Analysis of fibre size and shape distributions
- Progress meetings with industrial partner Ethos Environmental
Global Wheat Detection (Kaggle Competition)
Published:
- Implementation of various Cut and Mix plus Style Transfer image augmentations
- Single-class object detection using EfficientDet
Predicting AirBnb Prices in Athens using Machine Learning
Published:
- Data Preprocessing
- Feature Engineering
- Regression using Random Forest, XGBoost
Real-time Bolt Detection Using Deep Learning
Published:
- Development of a YOLOv5 deep learning bolt detector
- Real-time bolt detection using ZED 2i camera and Edge AI Gateway
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Automatic Annotation of Subsea Pipelines Using Deep Learning
Published in MDPI Sensors, 2020
The paper presents an automatic image annotation framework that identifies/classifies key events of interest in subsea pipelines survey video.
Recommended citation: Stamoulakatos, A.; Cardona, J.; McCaig, C.; Murray, D.; Filius, H.; Atkinson, R.; Bellekens, X.; Michie, C.; Andonovic, I.; Lazaridis, P.; Hamilton, A.; Hossain, M.M.; Di Caterina, G.; Tachtatzis, C. "Automatic Annotation of Subsea Pipelines Using Deep Learning." Sensors 2020, 20, 674. https://www.mdpi.com/1424-8220/20/3/674
A Comparison of the Performance of 2D and 3D Convolutional Neural Networks for Subsea Survey Video Classification
Published in OCEANS 2021, 2021
The paper presents an automatic image annotation framework that identifies/classifies key events of interest in subsea pipelines survey video.
Recommended citation: A. Stamoulakatos et al., "A Comparison of the Performance of 2D and 3D Convolutional Neural Networks for Subsea Survey Video Classification," OCEANS 2021: San Diego – Porto, 2021, pp. 1-10, doi: 10.23919/OCEANS44145.2021.9706125. https://ieeexplore.ieee.org/document/9706125
talks
teaching
Private Maths/Physics Tutoring
Private Tutoring, , 2015
- Assisted high school students with maths and physics exercises.
C++ Teaching Assistant
Undergraduate Course, University of Strathclyde, EEE Department, 2018
- Assisted 2nd year students in C++ lab exercises and final project
- Taught fundamentals of coding and object oriented programming