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You Only Look One: Unified, Real-Time Object Detection

Architecture

loss

Gambar 2. Arsitektur YOLOv1 [1].

Deskripsi:

  • Input: 448 x 488 x 3
  • Output: 7 * 7 * 30
  • Ukuran split (S): 7
  • Jumlah bounding box: 2
  • Jumlah kelas: 20

Hasil prediksi diencode sebagai S x S x (B * 5 + C)

Loss

loss

Gambar 2. Fungsi loss YOLOv1 [1].

Deskripsi:

  • Baris pertama dan kedua, loss untuk kesalahan predikdi koordinat (x, y, width, height).
  • Baris ketiga, loss untuk kesalahan iou score untuk sel yang ada objek.
  • Baris keempat, loss untuk kesalahan iou score untuk sel yang tidak ada objek.
  • Baris kelima, loss untuk kesalahan klasifikasi
  • Lambda_coord, bobot untuk loss koordinat, sebesar 5.
  • Lambda_noobj, bobot untuk kesalahan iou score untuk sel yang tidak ada objek.

Perhitungan loss menggunakan sum-squared error.

Refrensi

[1] https://arxiv.org/abs/1506.02640

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