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Algoritma Komputer Deteksi & Indentifikasi Satwa Liar

Ahli biologi Derek E. Lee pada Penn State University dan ilmuwan utama Wild Nature Institute bekerjasama dengan ahli cloud computing pada Microsoft Azure di Amerika Serikat, membuat teknologi algoritma komputer (machine-learning) untuk otomatisasi identifikasi obyek pada riset-riset satwa-satwa liar. Metode ini berguna bagi peneliti yang mempelajari pola-pola unik identifikasi fauna seperti kucing liar, gajah, salamander, ikan, pinguin, dan mamalia laut (Science Daily, 11/2/2019).

“Many researchers need to identify and collect data on specific individuals in their work, for example to estimate survival, reproduction, and movement. Instead of tags and other human-applied markings that could interfere with the animal's behavior, many researchers take photographs of the animal's unique markings. We have pattern recognition software to help analyze these photos, but the photos all have to be manually prepared for analysis. Because we often have thousands of photos to go thorough, this creates a serious bottleneck,” ungkap Derek E. Lee (Penn State University/PSU, 11/2/2019).

Teknologi machine-learning baru itu dapat menghasilkan foto-foto yang dapat digunakan dalam berbagai riset dan analisis satwa liar. Biolog Lee menggunakan foto-foto guna mempelajari kelahiran, kematian, dan pergerakan lebih dari 3.000 zarafah di Afrika Timur. Lee dan timnya merekam dengan foto digital keunikan hewan dan pola-pola spot yang tdak berubah guna identifikasi kelahiran, kematian, dan pergerakannya.  Hasil riset itu dirilis oleh Ecological Informatics edisi awal 2019 (Patrick Buehler, Bill Carroll, Ashish Bhatia, Vivek Gupta, Derek E. Lee, “An automated program to find animals and crop photographs for individual recognition,” Ecological Informatics, 2019).

“The system achieves near-perfect recognition of giraffe torsos without expensive hardware requirements like a dedicated high-powered graphics processing unit. It is wonderful how the Azure team automated this tedious aspect of our work. It used to take us a week to process our new images after a survey, and now it is done in minutes. This system moves us closer to fully automatic animal identification from photos,” ujar Lee (PSU, 11/2/2019).

Oleh: Servas Pandur