Repozytorium PJATK

Development of an Automated Image Recognition Framework of Lynxes in Camera Traps in Poland

Repozytorium Centrum Otwartej Nauki

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dc.contributor.author Boujbel, Asma
dc.date.accessioned 2023-01-09T13:58:20Z
dc.date.available 2023-01-09T13:58:20Z
dc.date.issued 2023-01-09
dc.identifier.issn 2022/M/AM/4
dc.identifier.uri https://repin.pjwstk.edu.pl/xmlui/handle/186319/2164
dc.description.abstract Since 1994 Lynx are under strict species protection and is part of the Polish Red Book of Animals (Polska czerwona ksiega zwierzat), therefore plenty of measures were taken to preserve and care for this pro- tected species. A monitoring system, including several camera traps, of wild animals in their natural habitat was expanded to include Lynx. This system generates data of wildlife continuously and in large volume which relies on citizen scientists to manually process images and videos cap- tured from camera traps. The process can be extremely time consuming and laborious. Leveraging the recent advances in deep learning techniques and computer vision, we overcome this obstacle with the idea of devel- oping an automated framework to automatically identify and recognize Lynx in the wild. We kick o this project by using a sample dataset of Lynx images from the National Park to nd the most accurate image recognition model. First by assessing three di erent state-of-the-art deep learning algorithms using Transfer Learning methods then by training our own benchmark Convolutional Neural Network models using three complementary architectures. The results later were compared and dis- cussed taking into account the accuracy and speed of each method. In turn, a proposal concerning the model with the best performance for fur- ther testing and implementation was introduced. And nally we re ect on our work by structuring an improvement plan and planning future stages in this project. pl_PL
dc.language.iso en pl_PL
dc.relation.ispartofseries ;Nr 6411
dc.subject animal recognition pl_PL
dc.subject convolutional neural networks pl_PL
dc.subject deep learning pl_PL
dc.subject computer vision pl_PL
dc.subject wildlife monitoring pl_PL
dc.title Development of an Automated Image Recognition Framework of Lynxes in Camera Traps in Poland pl_PL
dc.type Thesis pl_PL


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