Re-Identifikasi Harimau Amur Menggunakan CNN

christian, Niko (2021) Re-Identifikasi Harimau Amur Menggunakan CNN. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Memelihara keanekaragaman spesies merupakan salah satu cara dalam menjaga lingkungan. Data dari WWF menyebutkan bahwa salah satu hewan yang terancam punah adalah harimau amur. Meskipun pada tahun 2010 harimau amur mengalami krisis, tetapi populasi hewan ini kembali naik berkat program TX2. Semakin banyaknya populasi memberi tantangan tersendiri untuk mengawasi pergerakan hewan ini. Metode kalung transmisi dirasa kurang sesuai karena potensi gagalnya pengiriman sinyal dan mahalnya upah buruh. Visi komputer dapat menjadi inovasi untuk mengawasi harimau menggunakan kamera ataupun transportasi udara. Metode yang digunakan pada model adalah CNN. Pada akhirnya model akan menghasilkan distance matrix sebagai bahan re-identifikasi. Dengan mencoba beberapa model CNN, penelitian ini diharapkan dapat membantu mengembangkan sistem visi komputer yang telah ada ==================================================================================================== Maintaining species diversity is one method to protect the enviro- nment. Data From WWF states if amur tiger is one of endangered animals right now. Even though in 2010 the amur tiger experienced a crisis, the population of this animal has increased again thanks to the TX2 program. The increasing number of populations presents its own challenges to monitor the movement of these animals. The transmission necklace method was deemed unsuitable due to the po- tential for failed signal transmissions and the high labor's payment. Computer vision can be an innovation to monitor tigers using came- ras or air transportation.The method that will be used in the model is CNN. In the end, the model will produce distance matrix as ma- terial for re-identi�cation. With trying several CNN models, this research is expected to help the development of existing computer vision systems. This system is built based on existing datasets and re-identi�cation references.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: CNN, Amur Tiger, Re-Identification CNN, Harimau Amur, Re-Identifikasi
Subjects: Q Science
Q Science > QA Mathematics > QA76.758 Software engineering
Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
Divisions: Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User: NIko Christian Budi Putra
Date Deposited: 31 Aug 2021 02:28
Last Modified: 31 Aug 2021 02:28
URI: https://repository.its.ac.id/id/eprint/91082

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