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Journal : computer science co-science

Enhancing FOMAML with Domain-Specific Residual Pretraining for Few-Shot Chili Disease Classification Rizal Amegia Saputra; Agus Buono; Karlisa Priandana; Samsuzana Abd Aziz; Muhamad Syukur
Computer Science (CO-SCIENCE) Vol. 6 No. 2 (2026): July 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/co-science.v6i2.13101

Abstract

Meta-learning is an approach designed to address data limitations in few-shot learning scenarios. The performance of meta-learning is influenced by the quality of the initial weights used during the meta-training process. Initial weights derived from a relevant domain have the potential to produce more informative feature representations, thereby enabling the adaptation process to new tasks to proceed more effectively. This study analyzes the impact of domain-specific pretrained initialization on classification performance, learning stability, convergence behavior, and computational trade-offs within the First-Order Model-Agnostic Meta-Learning (FOMAML) framework using an enhanced ResNet-50 backbone. Experiments were conducted on a 3-way classification scenario with 1-shot, 5-shot, and 10-shot configurations. Model evaluation was performed using accuracy, precision, recall, and F1-score, while learning stability was analyzed using standard deviation (Std) and coefficient of variation (CV). The experimental results show that a chili-domain pretrained initialization consistently yields better performance than random initialization. Accuracy reached 95.33%, 95.60%, and 95.94% in the 1-shot, 5-shot, and 10-shot scenarios, respectively an increase of 17.20, 12.61, and 17.49 percentage points compared to random initialization. In terms of stability, the CV values decreased to 1.00%, 0.59%, and 1.03%, compared to 1.10%, 3.66%, and 2.42% with random initialization. These performance improvements were achieved with relatively small differences in training time 0.056 minutes, 0.170 minutes, and 0.876 minutes for the 1-shot, 5-shot, and 10-shot scenarios, respectively. Domain-specific pretrained initialization produces more relevant initial feature representations, thereby improving the effectiveness and stability of FOMAML adaptation while maintaining computational requirements comparable to those of random initialization
Co-Authors Ade Fruandta Adi Rakhman Aditya Cipta Raharja Agung Prajuhana Putra Akhmad Faqih Akhmad Faqih Alif Kurniawan Alvin Fatikhunnada Anang Kurnia Angga Wahyu Pratama Aries Maesya Arif Imam Suroso Arini Aha Pekuwali Arini Pekuwali Astuti, Indah Puji Atik Pawestri Sulistyo Aziz Kustiyo Aziz Rahmad Bahukeling, Trukan Sri Benyamin Kusumoputro Bib Paruhum Silalahi Budi Nugroho Cece Sumantri DEWI APRI ASTUTI Dhany Nugraha Ramdhany Dian Kartika Utami Edi Santosa EFFENDI TRI BAHTIAR Ekowati Handharyani Endang Purnama Giri Erliza Hambali Erliza Noor Ernan Rustiadi Fadhilah Syafria Fajar Delli Wihartiko Farahnugraha Makkuraga Fildza Novadiwanti Firdaus, Husni Firdaus, Nova Fredicia Fredicia Galih Kurniawan Sidik Galih Kurniawan Sidik Galih Kurniawan Sidik Gendut Suprayitno Gita Adhani GUNARSO GUNARSO Hardhienata, Medria Kusuma Dewi Harry Dhika Hartoyo Hartoyo Hastuadi Harsa Herianto Herianto Heru Sukoco Hidayat Hidayat Hidayat I Wayan Astika Ibrahim, Firmansyah Iis Rodiah Imas Sukaesih Sitanggang Indah Prasasti Indah Puji Astuti Indra Jaya Inggih Permana Irman Hermadi Irmansyah . Irsal Las Irsal Las ISKANDAR ZULKARNAEN SIREGAR Jemsri Stenli Batlajery Kana Saputra S Karlisa Priandana Kikin H Mutaqin Kudang Boro Seminar Laila Sari Lubis Laila Sari Lubis Lailan Syaufina Lidya Ningsih Lilik Noor Yuliati Lina Karlinasari Liyantono Luh Kesuma Wardhani Lumalessil, Ferry Lodewik Luthfan Almanfaluthi M. Cholid Mawardi M. MIFTAH RAHMAN M. Mukhlis Marcelita, Faldiena Mindara, Gema Parasti Mohamad Solahudin Muhammad Adib Zamzam Muhammad Ardiansyah Muhammad Rafi Muttaqin Mushthofa Mushthofa Mustakim Mustakim Mustakim Mustakim Muttaqin, Muhammad Rafi Niswati, Za'imatun Noviyanti, Inna Nurhayati, Yosi Popong Nurhayati Pratistya, Sayu Desty Puspita Kartika Sari Puspita Kartika Sari Putri Yuli Utami Raehan, Siti Raharja, Aditya Cipta Rahmat Hidayat Rangga Pebrianto Rangga Rizal Amegia Saputra Rizal Syarief Rizaldi Boer Rizki, Arviani RR. Ella Evrita Hestiandari Samsuzana Abd Aziz Santo, Deni Sanusi Sanusi Sari Agustini Hafman Savitri, Siska Shelvie Nidya Neyman Sholihah, Walidatush Sidik, Galih Kurniawan Siregar, Ardinsyah Sitanggang, Imas S. SITI CHUROTUL AINI Siti Churotul Aini Siti Kania Kushadiani Sony Hartono Wijaya Sri Dianing Asri SRI HENDRASTUTI HIDAYAT Sri Nurdiati Sri Wahjuni Stephane Douady Suharno Suharno Suharno Sumanto Sumanto Syeiva Nurul Desylvia Taufik Djatna Thoyyibah Tanjung Toto Haryanto Trukan Sri Bahukeling ULFA ADZKIA Ulfa Adzkia Uliniansyah, Mohammad Teduh Vicky Zilvan Wisnu Ananta Kusuma Wisnu Jatmiko Woro Estiningtyas Woro Estiningtyas Woro Estiningtyas Yan Mitha Djaksana Yandra Arkeman Yani Nurhadryani Yenni Vetrita Yoanda, Sely