Karya
Judul/Title Fine-tuning deep neural network for saliency prediction in movie poster documents
Penulis/Author Kristian Adi Nugraha (1); Dr.Eng. Ir. Igi Ardiyanto, S.T., M.Eng. (2); Dr.Eng. Ir. Sunu Wibirama, S.T., M.Eng., IPM. (3)
Tanggal/Date 28 2025
Kata Kunci/Keyword
Abstrak/Abstract Saliency prediction models are typically trained on natural images, focusing on features such as shape and color. However, predicting saliency in images with text is challenging because the human brain processes text differently than it processes visual objects. To address this research gap, we fine-tuned a saliency model to improve the accuracy of images containing text, specifically, movie posters. Our fine-tuned model — based on GSGNet and TranSalNet — outperformed the original models in predicting the saliency map for movie posters. The experimental results indicate that text elements exhibit patterns that can be learned for better saliency prediction.
Rumpun Ilmu Teknik Elektro
Bahasa Asli/Original Language English
Level Internasional
Status
Dokumen Karya
No Judul Tipe Dokumen Aksi
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