Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Fahimeh Farahnakian"'
Autor:
Fahimeh Farahnakian, Farshad Farahnakian, Stefan Björkman, Victor Bloch, Matti Pastell, Jukka Heikkonen
Publikováno v:
Journal of Agriculture and Food Research, Vol 16, Iss , Pp 101067- (2024)
Automatic and real-time pose estimation is important in monitoring animal behavior, health, and welfare. In this paper, we utilized pose estimation for monitoring the farrowing process to prevent piglet mortality and preserve the health and welfare o
Externí odkaz:
https://doaj.org/article/cc50e6e8b20841b2b3229c7882d2e44d
Publikováno v:
Journal of Agriculture and Food Research, Vol 15, Iss , Pp 100890- (2024)
Accurate and efficient automated rice grain classification systems are vital for rice producers, distributors, and traders, offering improved quality control, cost optimization, and supply chain management. They also hold the potential to aid in the
Externí odkaz:
https://doaj.org/article/9ee0be1144094200b5199073f0453811
Autor:
Dipak Kumar Nidhi, Iiro Seppä, Fahimeh Farahnakian, Luca Zelioli, Jukka Heikkonen, Rajeev Kanth
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 34, Iss 1, Pp 135-https://youtu.be/Xy11Pp1AEWg (2023)
Minerals prospects mapping plays a pivotal role in the sustainable development of mineral resources, offering critical insights into subsurface geology and mineral potential. Traditional geological methods are often labor-intensive and time-consuming
Externí odkaz:
https://doaj.org/article/ebb00a006c2445e5a34c885a6fa886ac
Autor:
Farshad Farahnakian, Florent Nicolas, Fahimeh Farahnakian, Paavo Nevalainen, Javad Sheikh, Jukka Heikkonen, Csaba Raduly-Baka
Publikováno v:
Remote Sensing, Vol 15, Iss 6, p 1477 (2023)
Abnormal behavior detection is currently receiving much attention because of the availability of marine equipment and data allowing maritime agents to track vessels. One of the most popular tools for developing an efficient anomaly detection system i
Externí odkaz:
https://doaj.org/article/f52b91a14c5f4c0e9050cd641a30cf07
Autor:
Fahimeh Farahnakian, Jukka Heikkonen
Publikováno v:
Remote Sensing, Vol 12, Iss 16, p 2509 (2020)
Object detection is a fundamental computer vision task for many real-world applications. In the maritime environment, this task is challenging due to varying light, view distances, weather conditions, and sea waves. In addition, light reflection, cam
Externí odkaz:
https://doaj.org/article/1045511b6c7c43b18b3a684ea4b82444
Autor:
Fahimeh Farahnakian, Stefan Björkman, Farshad Farahnakian, Victor Bloch, Matti Pastell, Jukka Heikkonen
Automatic and real-time pose estimation is important in monitoring animal behavior, health and welfare. In this paper, we utilized pose estimation for monitoring farrowing process to prevent piglet mortality and preserve the health and welfare of sow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cf42d427238f7049a880f535b8877ff
https://doi.org/10.20944/preprints202304.1031.v1
https://doi.org/10.20944/preprints202304.1031.v1
Publikováno v:
2021 11th International Conference on Intelligent Control and Information Processing (ICICIP).
Autor:
Jukka Heikkonen, Fahimeh Farahnakian
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811633560
Advances in Intelligent Systems and Computing
Advances in Intelligent Systems and Computing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::565eafaf9684aedeaec890eda3c5254f
https://doi.org/10.1007/978-981-16-3357-7_3
https://doi.org/10.1007/978-981-16-3357-7_3
Publikováno v:
2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).
Automatic athlete pose estimation from images has recently received considerable attention from the computer vision community to understand the correct pose of athletes during training or competitions. However, human pose estimation from images or vi
Publikováno v:
ITSC
Reliable vessel detection can improve safety and security in maritime environment. Recently, application of Deep Learning (DL)-based detectors have become popular in autonomous vehicles. The aim of this paper is to study how much a pretrained DL mode