DETAIL KOLEKSI

Wildlife identification system using deep residual classifiers


Oleh : Abdul Rochman

Info Katalog

Status Verifikasi : Sudah

Link :

Subyek : Image processing

Penerbit : FTI - Usakti

Kota Terbit : Jakarta

Tahun Terbit : 2021

Halaman : 6 p.


File Repositori
No. Nama File Ukuran (KB) Status
1. 2021_MD_STF_Wildlife-Identification-System.pdf 0.29

C Camera-trap was used by several researchers toautomatically detect wildlife animal objects. Surprisingly, none ofresearcher observed wildlife animal particularly in Indonesia. In thisresearch, Deep Convolutional Neural Network was used in order toobtain accuracy of wildlife animal in Indonesia. TEAM datasets wasused and modified adjusting with wildlife animal in Indonesia, theresult of this study: accuracy of algorithm to tiger and elephant aswildlife animal in Indonesia reached 62.5% and 77% respectively.Hopefully the result can be generated in large-scale camera-trap.

C Camera-trap was used by several researchers toautomatically detect wildlife animal objects. Surprisingly, none ofresearcher observed wildlife animal particularly in Indonesia. In thisresearch, Deep Convolutional Neural Network was used in order toobtain accuracy of wildlife animal in Indonesia. TEAM datasets wasused and modified adjusting with wildlife animal in Indonesia, theresult of this study: accuracy of algorithm to tiger and elephant aswildlife animal in Indonesia reached 62.5% and 77% respectively.Hopefully the result can be generated in large-scale camera-trap.

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