Posts by Collection

CV

Here you can find my up-to-date curriculum vitae.

Improving the Safety, Reliability, and Efficiency of Cargo Transportation using Deep Learning

Published: October 01, 2019

• 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: October 01, 2019

• 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: October 01, 2020

• 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: October 01, 2021

• Data Preprocessing
• Feature Engineering
• Regression using Random Forest, XGBoost

Real-time Bolt Detection Using Deep Learning

Published: January 01, 2022

• Development of a YOLOv5 deep learning bolt detector
• Real-time bolt detection using ZED 2i camera and Edge AI Gateway

Portfolio item number 1

Short description of portfolio item number 1

Portfolio item number 2

Short description of portfolio item number 2

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

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