Swin-BiLSTM with Attention for Face Swap Detection in Deepfake Videos - Dalam bentuk pengganti sidang - Artikel Jurnal
NUR FITRI LUKITANIA
Informasi Umum
Kode
25.04.378
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Cyber Security
Dilihat
87 kali
Informasi Lainnya
Abstraksi
Digital manipula on tools like deepfakes have ad vanced in sophis ca on because to the quick development of deep learning and ar ficial intelligence. Face swapping, in which one person’s face is swapped out for another, is one of the most alarming types of deepfakes. This technique produces incredibly lifelike movies that may deceive viewers. Detec ng these manipulated videos is crucial to mi ga ng their nega ve impact on privacy and security. This paper proposes an ensemble approach to detec ng face swap deepfakes by combining the Swin Transformer and Bidirec onal Long Short-Term Memory (BiLSTM) with an a en on mechanism. The Swin Transformer is employed for spa al feature extrac on, while the BiLSTM captures temporal pa erns between frames, and the a en on mechanism focuses on the most relevant mesteps. The model is evaluated on the FaceForensics++ dataset, achieving a valida on accuracy of 93.81% with a valida on loss of 0.19, outperforming the Long Short-Term Memory (LSTM), Fully Convolu onal Network (FCN
- CII3E3 - KEAMANAN SIBER
- CS3243 - KECERDASAN MESIN DAN ARTIFISIAL
- CCH4D4 - TUGAS AKHIR
Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
Anda harus log in untuk mengakses flippingbook
Pengarang
| Nama | NUR FITRI LUKITANIA |
| Jenis | Perorangan |
| Penyunting | Vera Suryani |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2025 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
