Learning through Decision Tree in Simulated Soccer Environment. - Fahimeh Farahnakian; Nasser Mozayani (CIS (2), 2008)

Reinforcement Learning for Soccer Multi-agents System. - Fahimeh Farahnakian; Nasser Mozayani (CIS (2), 2009)

Q-learning based congestion-aware routing algorithm for on-chip network. - Fahimeh Farahnakian; Masoumeh Ebrahimi; Masoud Daneshtalab; Pasi Liljeberg; Juha Plosila (NESEA, 2011)

Optimized Q-learning model for distributing traffic in on-Chip Networks. - Fahimeh Farahnakian; Masoumeh Ebrahimi; Masoud Daneshtalab; Juha Plosila; Pasi Liljeberg (NESEA, 2012)

HARAQ: Congestion-Aware Learning Model for Highly Adaptive Routing Algorithm in On-Chip Networks. - Masoumeh Ebrahimi; Masoud Daneshtalab; Fahimeh Farahnakian; Juha Plosila; Pasi Liljeberg; Maurizio Palesi; Hannu Tenhunen (NOCS, 2012)

Adaptive reinforcement learning method for networks-on-chip. - Fahimeh Farahnakian; Masoumeh Ebrahimi; Masoud Daneshtalab; Juha Plosila; Pasi Liljeberg (ICSAMOS, 2012)

LiRCUP: Linear Regression Based CPU Usage Prediction Algorithm for Live Migration of Virtual Machines in Data Centers. - Fahimeh Farahnakian; Pasi Liljeberg; Juha Plosila (EUROMICRO-SEAA, 2013)

Energy Aware Consolidation Algorithm Based on K-Nearest Neighbor Regression for Cloud Data Centers. - Fahimeh Farahnakian; Tapio Pahikkala; Pasi Liljeberg; Juha Plosila (UCC, 2013)

Energy-Aware Dynamic VM Consolidation in Cloud Data Centers Using Ant Colony System. - Fahimeh Farahnakian; Adnan Ashraf; Pasi Liljeberg; Tapio Pahikkala; Juha Plosila; Ivan Porres; Hannu Tenhunen (IEEE CLOUD, 2014)

Hierarchical Agent-Based Architecture for Resource Management in Cloud Data Centers. - Fahimeh Farahnakian; Tapio Pahikkala; Pasi Liljeberg; Juha Plosila (IEEE CLOUD, 2014)

Hierarchical VM Management Architecture for Cloud Data Centers. - Fahimeh Farahnakian; Pasi Liljeberg; Tapio Pahikkala; Juha Plosila; Hannu Tenhunen (CloudCom, 2014)

Multi-agent Based Architecture for Dynamic VM Consolidation in Cloud Data Centers. - Fahimeh Farahnakian; Tapio Pahikkala; Pasi Liljeberg; Juha Plosila; Hannu Tenhunen (EUROMICRO-SEAA, 2014)

Energy-Efficient Virtual Machines Consolidation in Cloud Data Centers Using Reinforcement Learning. - Fahimeh Farahnakian; Pasi Liljeberg; Juha Plosila (PDP, 2014)

Bi-LCQ: A low-weight clustering-based Q-learning approach for NoCs. - Fahimeh Farahnakian; Masoumeh Ebrahimi; Masoud Daneshtalab; Pasi Liljeberg; Juha Plosila (Microprocess. Microsystems, 2014)

Adaptive load balancing in learning-based approaches for many-core embedded systems. - Fahimeh Farahnakian; Masoumeh Ebrahimi; Masoud Daneshtalab; Pasi Liljeberg; Juha Plosila (J. Supercomput., 2014)

Utilization Prediction Aware VM Consolidation Approach for Green Cloud Computing. - Fahimeh Farahnakian; Tapio Pahikkala; Pasi Liljeberg; Juha Plosila; Hannu Tenhunen (CLOUD, 2015)

Using Ant Colony System to Consolidate VMs for Green Cloud Computing. - Fahimeh Farahnakian; Adnan Ashraf; Tapio Pahikkala; Pasi Liljeberg; Juha Plosila; Ivan Porres; Hannu Tenhunen (IEEE Trans. Serv. Comput., 2015)

Self-Adaptive Resource Management System in IaaS Clouds. - Fahimeh Farahnakian; Rami Bahsoon; Pasi Liljeberg; Tapio Pahikkala (CLOUD, 2016)

A deep auto-encoder based approach for intrusion detection system. - Fahimeh Farahnakian; Jukka Heikkonen (ICACT, 2018)

Object Detection Based on Multi-sensor Proposal Fusion in Maritime Environment. - Fahimeh Farahnakian; Mohammad Hashem Haghbayan; Jonne Poikonen; Markus Laurinen; Paavo Nevalainen; Jukka Heikkonen (ICMLA, 2018)

An Efficient Multi-sensor Fusion Approach for Object Detection in Maritime Environments. - Mohammad Hashem Haghbayan; Fahimeh Farahnakian; Jonne Poikonen; Markus Laurinen; Paavo Nevalainen; Juha Plosila; Jukka Heikkonen (ITSC, 2018)

Visible and Infrared Image Fusion Framework based on RetinaNet for Marine Environment. - Fahimeh Farahnakian; Jussi Poikonen; Markus Laurinen; Dimitrios Makris 001; Jukka Heikkonen (FUSION, 2019)

Deep Convolutional Neural Network-based Fusion of RGB and IR Images in Marine Environment. - Fahimeh Farahnakian; Jussi Poikonen; Markus Laurinen; Jukka Heikkonen (ITSC, 2019)

Comparative Analysis of Image Fusion Methods in Marine Environment. - Fahimeh Farahnakian; Parisa Movahedi; Jussi Poikonen; Eero Lehtonen; Dimitrios Makris 001; Jukka Heikkonen (ROSE, 2019)

Energy-Aware VM Consolidation in Cloud Data Centers Using Utilization Prediction Model. - Fahimeh Farahnakian; Tapio Pahikkala; Pasi Liljeberg; Juha Plosila; Nguyen Trung Hieu; Hannu Tenhunen (IEEE Trans. Cloud Comput., 2019)

Fusing LiDAR and Color Imagery for Object Detection using Convolutional Neural Networks. - Fahimeh Farahnakian; Jukka Heikkonen (FUSION, 2020)

Comparing CNN-Based Object Detectors on Two Novel Maritime Datasets. - Valentin Soloviev; Fahimeh Farahnakian; Luca Zelioli; Bogdan Iancu; Johan Lilius; Jukka Heikkonen (ICME Workshops, 2020)

A Comparative Study of Deep Learning-based RGB-depth Fusion Methods for Object Detection. - Fahimeh Farahnakian; Jukka Heikkonen (ICMLA, 2020)

RGB-depth Fusion Framework for Object Detection in Autonomous Vehicles. - Fahimeh Farahnakian; Jukka Heikkonen (ICSPCS, 2020)

Deep Learning Based Multi-Modal Fusion Architectures for Maritime Vessel Detection. - Fahimeh Farahnakian; Jukka Heikkonen (Remote. Sens., 2020)

Towards Autonomous Industrial Warehouse Inspection. - Fahimeh Farahnakian; Lauri Koivunen; Tuomas Mäkilä; Jukka Heikkonen (ICAC, 2021)

Transfer Learning for Maritime Vessel Detection using Deep Neural Networks. - Fahimeh Farahnakian; Luca Zelioli; Jukka Heikkonen (ITSC, 2021)

Short and Long Term Vessel Movement Prediction for Maritime Traffic. - Farshad Farahnakian; Fahimeh Farahnakian; Javad Sheikh; Paavo Nevalainen; Jukka Heikkonen (critis, 2023)

Enhancing Minerals Prospects Mapping with Machine Learning: Addressing Imbalanced Geophysical Datasets and Data Visualization Approaches. - Dipak Kumar Nidhi; Iiro Seppä; Fahimeh Farahnakian; Luca Zelioli; Jukka Heikkonen; Rajeev Kumar Kanth (FRUCT, 2023)

Multistream Convolutional Neural Network Fusion for Pixel-wise Classification of Peatland. - Fahimeh Farahnakian; Luca Zelioli; Timo P. Pitkänen; Jonne Pohjankukka; Maarit Middleton; Sakari Tuominen; Paavo Nevalainen; Jukka Heikkonen (FUSION, 2023)

Ice-Water Segmentation Using Deep Convolutional Neural Network-Based Fusion Approach. - Javad Sheikh; Fahimeh Farahnakian; Farshad Farahnakian; Jukka Heikkonen (ICAC, 2023)

Sea Ice Concentration Estimation Via Fusion of Sentinel-1 and AMSR2 Based on Encoder-Decoder Architecture. - Javad Sheikh; Fahimeh Farahnakian; Farshad Farahnakian; Jukka Heikkonen (ITSC, 2023)

CNN-based Boreal Peatland Fertility Classification from Sentinel-1 and Sentinel-2 Imagery. - Fahimeh Farahnakian; Luca Zelioli; Maarit Middleton; Iiro Seppä; Timo P. Pitkänen; Jukka Heikkonen (ROSE, 2023)

A Comprehensive Study of Clustering-Based Techniques for Detecting Abnormal Vessel Behavior. - Farshad Farahnakian; Florent Nicolas; Fahimeh Farahnakian; Paavo Nevalainen; Javad Sheikh; Jukka Heikkonen; Csaba Raduly-Baka (Remote. Sens., 2023)

Enhancing Peatland Classification using Sentinel-1 and Sentinel-2 Fusion with Encoder-Decoder Architecture. - Luca Zelioli; Fahimeh Farahnakian; Farshad Farahnakian; Maarit Middleton; Jukka Heikkonen (FUSION, 2024)

Multi-modal Fusion of LiDAR and PRISMA Data for Cobalt Mapping: A Case Study from the Áramo Mine, Spain. - Fahimeh Farahnakian; Farshad Farahnakian; Javad Sheikh; Steven Downey; Vaughan Williams; Jukka Heikkonen (ICPR (Workshops and Challenges, 4), 2024)

SEDA: Similarity-Enhanced Data Augmentation for Imbalanced Learning. - Javad Sheikh; Farshad Farahnakian; Fahimeh Farahnakian; Luca Zelioli; Jukka Heikkonen (ICPR (26), 2024)

A Comparative Study of Machine Learning Models for Pixel-Wise Acid Mine Drainage Classification Using Sentinel-2. - Fahimeh Farahnakian; Johanna Torppa; Nike Luodes; Hannu Panttila; Teemu Karlsson (IGARSS, 2024)

Machine Learning Algorithms for Acid Mine Drainage Mapping Using Sentinel-2 and Worldview-3. - Fahimeh Farahnakian; Nike Luodes; Teemu Karlsson (Remote. Sens., 2024)

An Ensemble Modeling Approach for Mapping Critical Mineral Distribution with LiDAR and PRISMA Data. - Fahimeh Farahnakian; Mahyar Yousefi; Ana Cláudia Teodoro (GISTAM, 2025)

S34I Project: Secure and Sustainable Supply of Raw Materials for EU Industry. - Ana Cláudia Teodoro; Joana Cardoso-Fernandes; Mihaela Gheorghe; Francesco Falabella; Fabiana Calò; Antonio Pepe 001; Delira Hanelli; Andreas Knobloch; Roberto De La Rosa; Fahimeh Farahnakian; Georgios Periklis Georgalas; Enoc Sanz-Ablanedo; et al. (GISTAM, 2025)

Peatland pixel-level classification via multispectral, multiresolution and multisensor data using convolutional neural network. - Luca Zelioli; Fahimeh Farahnakian; Maarit Middleton; Timo P. Pitkänen; Sakari Tuominen; Paavo Nevalainen; Jonne Pohjankukka; Jukka Heikkonen (Ecol. Informatics, 2025)

Enhancing hurdles athletes' performance analysis: A comparative study of cnn-based pose estimation frameworks. - Pouya Jafarzadeh; Luca Zelioli; Petra Virjonen; Fahimeh Farahnakian; Paavo Nevalainen; Jukka Heikkonen (Multim. Tools Appl., 2025)