Hand gesture recognition using adaptive network based fuzzy inference system and k-nearest neighbor
Fitri Utaminingrum (Faculty of Engineering, Universitas Indonesia, 2017)
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| The purpose of the study was to investigate hand gesture recognition. The hand gestures of American Sign Language are divided into three categories—namely, fingers gripped, fingers facing upward, and fingers facing sideways—using the adaptive network-based fuzzy inference system. The goal of the classification was to speed up the recognition process, since the process of recognizing the hand gesture takes a longer time. All pictures in all of the categories were recognized using K-nearest neighbor. The procedure involved taking real-time pictures without any gloves or censors. The findings of the study show that the best accuracy was obtained when the epochs score was 10. The proposed approach will result in more effective recognition in a short amount of time. |
| No. Panggil : | UI-IJTECH 8:3 (2017) |
| Entri utama-Nama orang : | |
| Subjek : | |
| Penerbitan : | Depok: Faculty of Engineering, Universitas Indonesia, 2017 |
| Sumber Pengatalogan : | LibUI eng rda |
| ISSN : | 20869614 |
| Majalah/Jurnal : | International Journal of Technology |
| Volume : | Vol. 8, No. 3, April 2017: Hal. 559-567 |
| Tipe Konten : | text |
| Tipe Media : | unmediated |
| Tipe Carrier : | volume |
| Akses Elektronik : | https://doi.org/10.14716/ijtech.v8i3.3146 |
| Institusi Pemilik : | Universitas Indonesia |
| Lokasi : | Perpustakaan UI, Lantai 4 R. Koleksi Jurnal |
| No. Panggil | No. Barkod | Ketersediaan |
|---|---|---|
| UI-IJTECH 8:3 (2017) | 08-23-03794118 | TERSEDIA |
| Ulasan: |
| Tidak ada ulasan pada koleksi ini: 9999920533906 |
