Fahimeh Farahnakian
PhD
fahimeh.farahnakian@utu.fi Vesilinnantie 5 Turku Työhuone: 4th floor,452CJ ORCID-tunniste: https://orcid.org/https://orcid.org/0000-0002-7672-9346?lang=en |
Asiantuntijuusalueet
Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Data Analysis, Autonomous Systems and Cloud Computing
Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Data Analysis, Autonomous Systems and Cloud Computing
Tutkimusyhteisö tai tutkimusaihe
Computer Science
Computer Science
Biografia
I am adjunct professor of Computer Science the University of Turku (UTU), Finland. From 2011-2016, I was a researcher and PhD candidate at the department of future technologies, University of Turku. I have worked in academia since 2009 in several positions such as research assistant, teacher assistant, post-doctoral researcher, lecturer and senior researcher. I have a proven ability in mentoring, proposal-writing, project management and state-of-the-art computer proficiencies.
I am adjunct professor of Computer Science the University of Turku (UTU), Finland. From 2011-2016, I was a researcher and PhD candidate at the department of future technologies, University of Turku. I have worked in academia since 2009 in several positions such as research assistant, teacher assistant, post-doctoral researcher, lecturer and senior researcher. I have a proven ability in mentoring, proposal-writing, project management and state-of-the-art computer proficiencies.
Tutkimus
I have worked in academia since 2009 in several positions such as research assistant, teacher assistant, post-doctoral researcher, lecturer and senior researcher. I jointed the University Turku as a research visitor in 2011 and then after 6 months I got an offer to start my Ph.D. During my Ph.D, I have also visited and worked the Birmingham University for almost half year in 2015. I have also worked at the Kingston University in London as a research visitor in 2019. I have collaborated with these universities and worked on various projects. These international research visits greatly helped me in building new connection for further international collaborations in many ways. Currently, I am working on several projects at UTU and supervising several M.Sc. student. My research interests include Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Data Analysis, Autonomous Systems and Cloud Computing. I have published +30 articles in journal and conference proceedings.
Opetus
I have 10+ years’ experience in teaching and research specializing in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Data Analysis, Autonomous Systems and Cloud Computing. You can find more information about my projects from my webpage.
Julkaisut 
1/3
- Enhancing hurdles athletes’ performance analysis: A comparative study of cnn-based pose estimation frameworks (2025)
- Multimedia Tools and Applications
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Maritime vessel movement prediction: A temporal convolutional network model with optimal look-back window size determination (2025)
- Multimodal transportation
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - S34I Project: Secure and Sustainable Supply of Raw Materials for EU Industry (2025) Proceedings of the 11th International Conference on Geographical Information Systems Theory, Applications and Management Teodoro, Ana Cláudia; Cardoso-Fernandes, Joana; Gheorghe, Mihaela; Falabella, Francesco; Calò, Fabiana; Pepe, Antonio; Hanelli, Delira; Knobloch, Andreas; De La Rosa, Roberto; Farahnakian, Fahimeh; Georgalas, Georgios Periklis; Sanz-Ablanedo, Enoc; Williams, Vaughan; Oštir, Krištof
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A comparative study of state-of-the-art deep learning architectures for rice grain classification (2024)
- Journal of agriculture and food research
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Addressing imbalanced data for machine learning based mineral prospectivity mapping (2024)
- Ore Geology Reviews
(A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä) - Enhancing Peatland Classification using Sentinel-1 and Sentinel-2 Fusion with Encoder-Decoder Architecture (2024) 2024 27th International Conference on Information Fusion (FUSION) Zelioli, Luca; Farahnakian, Fahimeh; Farahnakian, Farshad; Middleton, Maarit; Heikkonen, Jukka
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Machine Learning Algorithms for Acid Mine Drainage Mapping Using Sentinel-2 and Worldview-3 (2024)
- Remote Sensing
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Pose estimation of sow and piglets during free farrowing using deep learning (2024)
- Journal of agriculture and food research
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - SEDA: Similarity-Enhanced Data Augmentation for Imbalanced Learning (2024)
- Lecture Notes in Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Short and Long Term Vessel Movement Prediction for Maritime Traffic (2024)
- Lecture Notes in Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A Comprehensive Study of Clustering-Based Techniques for Detecting Abnormal Vessel Behavior (2023)
- Remote Sensing
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - CNN-based Boreal Peatland Fertility Classification from Sentinel-1 and Sentinel-2 Imagery (2023) 2023 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Farahnakian Fahimeh, Zelioli Luca, Middleton Maarit, Seppä Iiro, Pitkänen Timo P., Heikkonen Jukka
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Deep Learning and Computer Vision in Remote Sensing (2023) Farahnakian Fahimeh, Heikkonen Jukka, Jafarzadeh Pouya
(C2 Toimitustyö tieteelliselle kokoomateokselle) - Enhancing Minerals Prospects Mapping with Machine Learning: Addressing Imbalanced Geophysical Datasets and Data Visualization Approaches (2023)
- Proceedings of Conference of Open Innovations Association FRUCT
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Ice-Water Segmentation Using Deep Convolutional Neural Network-Based Fusion Approach (2023) The 28th International Conference on Automation and Computing: Digitalisation for Smart Manufacturing and Systems Sheikh Javad, Farahnakian Fahimeh, Farahnakian Farshad, Heikkonen Jukka
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Multistream Convolutional Neural Network Fusion for Pixel-wise Classification of Peatland (2023) 2023 26th International Conference on Information Fusion (FUSION) Farahnakian Fahimeh, Zelioli Luca, Pitkänen Timo, Pohjankukka Jonne, Middleton Maarit, Tuominen Sakari, Nevalainen Paavo, Heikkonen Jukka
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Real-Time Military Tank Detection Using YOLOv5 Implemented on Raspberry Pi (2023) 2023 the 4th International Conference on Artificial Intelligence, Robotics and Control (AIRC 2023) Jafarzadeh Pouya, Zelioli Luca, Farahnakian Fahimeh, Nevalainen Paavo, Heikkonen Jukka, Hemminki Petteri, Andersson Christian
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Sea Ice Concentration Estimation Via Fusion of Sentinel-1 and AMSR2 Based on Encoder-Decoder Architecture (2023)
- Proceedings of the IEEE international conference on intelligent transportation systems
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A Comparative Study of Deep Learning-based RGB-depth Fusion Methods for Object Detection (2021) 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA) Farahnakian Fahimeh, Heikkonen Jukka
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Driver Drowsiness Detection Using Deep Convolutional Neural Network (2021) 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Farahnakian Farshad, Leoste Janika, Farahnakian Fahimeh
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
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