Luca Zelioli

Addressing imbalanced data for machine learning based mineral prospectivity mapping (2024)

Ore Geology Reviews

Farahnakian, Fahimeh; Sheikh, Javad; Zelioli, Luca; Nidhi, Dipak; Seppä, Iiro; Ilo, Rami; Nevalainen, Paavo; Heikkonen, Jukka

(A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä)

Leveraging machine learning for maritime object detection and peatland classification : harnessing the power of machine learning for precise maritime object detection and peatland classification (2024)

Zelioli, Luca

(G5 Artikkeliväitöskirja)

Enhancing Peatland Classification using Sentinel-1 and Sentinel-2 Fusion with Encoder-Decoder Architecture (2024)

International Conference on Information Fusion

Zelioli, Luca; Farahnakian, Fahimeh; Farahnakian, Farshad; Middleton, Maarit; Heikkonen, Jukka

(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)

CNN-based Boreal Peatland Fertility Classification from Sentinel-1 and Sentinel-2 Imagery (2023)

IEEE International Symposium on Robotic and Sensors Environments

Farahnakian Fahimeh, Zelioli Luca, Middleton Maarit, Seppä Iiro, Pitkänen Timo P., Heikkonen Jukka

(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)

Real-Time Military Tank Detection Using YOLOv5 Implemented on Raspberry Pi (2023)

International Conference on Artificial Intelligence, Robotics and Control

Jafarzadeh Pouya, Zelioli Luca, Farahnakian Fahimeh, Nevalainen Paavo, Heikkonen Jukka, Hemminki Petteri, Andersson Christian

(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)

Enhancing Minerals Prospects Mapping with Machine Learning: Addressing Imbalanced Geophysical Datasets and Data Visualization Approaches (2023)

Conference of Open Innovations Association FRUCT, Proceedings of Conference of Open Innovations Association FRUCT

Nidhi Dipak Kumar, Seppä Iiro, Farahnakian Fahimeh, Zelioli Luca, Heikkonen Jukka, Kanth Rajeev

(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))

Multistream Convolutional Neural Network Fusion for Pixel-wise Classification of Peatland (2023)

International Conference on Information Fusion (FUSION)

Farahnakian Fahimeh, Zelioli Luca, Pitkänen Timo, Pohjankukka Jonne, Middleton Maarit, Tuominen Sakari, Nevalainen Paavo, Heikkonen Jukka

(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))

ABOships-An Inshore and Offshore Maritime Vessel Detection Dataset with Precise Annotations (2021)

Remote Sensing

Iancu Bogdan, Soloviev Valentin, Zelioli Luca, Lilius Johan

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Transfer Learning for Maritime Vessel Detection using Deep Neural Networks (2021)

IEEE International Intelligent Transportation Systems Conference, Proceedings of the IEEE international conference on intelligent transportation systems

Farahnakian Fahimeh, Zelioli Luca, Heikkonen Jukka

(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))

COMPARING CNN-BASED OBJECT DETECTORS ON TWO NOVEL MARITIME DATASETS (2020)

IEEE International Conference on Multimedia and Expo Workshops

Soloviev V, Farahnakian F, Zelioli L, Iancu B, Lilius J, Heikkonen J

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

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Addressing imbalanced data for machine learning based mineral prospectivity mapping (2024)

Leveraging machine learning for maritime object detection and peatland classification : harnessing the power of machine learning for precise maritime object detection and peatland classification (2024)

Enhancing Peatland Classification using Sentinel-1 and Sentinel-2 Fusion with Encoder-Decoder Architecture (2024)

CNN-based Boreal Peatland Fertility Classification from Sentinel-1 and Sentinel-2 Imagery (2023)

Real-Time Military Tank Detection Using YOLOv5 Implemented on Raspberry Pi (2023)

Enhancing Minerals Prospects Mapping with Machine Learning: Addressing Imbalanced Geophysical Datasets and Data Visualization Approaches (2023)

Multistream Convolutional Neural Network Fusion for Pixel-wise Classification of Peatland (2023)

ABOships-An Inshore and Offshore Maritime Vessel Detection Dataset with Precise Annotations (2021)

Transfer Learning for Maritime Vessel Detection using Deep Neural Networks (2021)

COMPARING CNN-BASED OBJECT DETECTORS ON TWO NOVEL MARITIME DATASETS (2020)