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Journal : journal of embedded systems security and intelligent systems

Analysis of Optimal Epoch Selection for YOLO26 Model in Detecting Graves and Free Slots Using UAV Photogrammetry Hafiz Irsyad; Muhammad Rizky Pribadi; Dedy Hermanto; Dina Lestari Putri
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 2 (2026): June 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i2.11573

Abstract

Purpose – This study investigates the optimal number of training epochs for the YOLO26 model in detecting graves and free burial slots from UAV photogrammetry imagery, with particular attention to model convergence, generalization, and detection performance. Design/methods/approach – A publicly available cemetery dataset containing two object classes, namely graves and free burial slots, was preprocessed using auto-orientation, 2×2 tiling, resizing to 640 × 640 pixels, grayscale conversion, and data augmentation. The YOLO26 model was trained using transfer learning under six epoch configurations: 50, 100, 150, 200, 250, and 300 epochs. Performance was evaluated using precision, recall, F1-score, mAP@50, mAP@50–95, confusion matrices, and training and validation loss curves. Findings – Model performance improved substantially as training progressed and began to stabilize after approximately 200 epochs. The highest observed performance occurred at epoch 289, with a precision of 98.78%, recall of 98.26%, F1-score of 99%, mAP@50 of 99.40%, and mAP@50–95 of 90.94%. Although the 300-epoch configuration produced similarly strong results, the additional gains were marginal, indicating diminishing returns after convergence. Research implications/limitations – The findings provide practical guidance for selecting an appropriate training duration in UAV-based cemetery mapping and small-object detection. However, the study relies on a relatively small, single-source dataset, which may limit generalizability across different cemetery layouts, environmental conditions, and UAV imaging configurations. Originality/value – This study provides a domain-specific multi-epoch benchmark for YOLO26 and demonstrates the importance of metric- and convergence-based checkpoint selection rather than relying solely on the maximum predefined number of epochs.
UAV Based Automated Surveillance of Ganoderma boninense in Oil Palm Canopies Using YOLO26 Architecture Muhammad Rizky Pribadi; Hafiz Irsyad; Eka Puji Widiyanto; Muhammad Tri Setianto; Safeti Intan Pratiwi
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 3 (2026): September 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i3.11502

Abstract

Purpose – This study develops and evaluates a UAV-based automated surveillance approach using the YOLO26 architecture to detect visible symptoms associated with Ganoderma boninense infection in oil palm canopies. The study addresses the limitations of conventional manual inspection and multi-stage detection systems by applying a unified single-stage object-detection framework. Design/methods/approach – The model was developed using a publicly available dataset containing 1,133 annotated UAV images of oil palm canopies. Images were preprocessed, augmented, and partitioned using a plantation-block-aware strategy to reduce spatial data leakage. YOLO26s was trained using the Ultralytics framework on an NVIDIA Tesla T4 GPU. Model performance was evaluated using precision, recall, mAP@50, mAP@50–95, confidence-threshold sensitivity analysis, precision–recall curves, and five-fold block-aware cross-validation. Findings – On the independent block-aware test set of 118 images, the model achieved an mAP@50 of 77.14%, mAP@50–95 of 41.98%, precision of 66.03%, and recall of 76.32%. Five-fold block-aware cross-validation produced a mean mAP@50 of 74.12% ± 5.51% and a mean mAP@50–95 of 41.31% ± 4.00%. The relatively high recall indicates that the model can identify most visible infection instances, although its moderate precision shows that false-positive detections remain a practical concern. Research implications/limitations – The findings demonstrate the potential of YOLO26 to support UAV-based oil palm disease surveillance and targeted field inspection. However, the study relies on a single public dataset with inherited annotation procedures, lacks geographically independent external validation, and does not include direct benchmarking on onboard UAV or embedded edge devices. Originality/value – This study provides an early empirical evaluation of YOLO26 for UAV-based detection of visible Ganoderma symptoms in oil palm canopies. Its contribution lies in combining a single-stage detection architecture with plantation-block-aware evaluation, threshold-sensitivity analysis, and cross-validation to provide a more leakage-controlled assessment of model performance.
Co-Authors -, Felicia Adi Saputra Aditya Al Assad Aditya Ali Kusuma Adrian Chen Adrian Suparto Adrian Suparto Ahmad Dumyati Ahmad Zaky Nadimsyah Albert Cahayadi Alvin Hujaya Alwin Marcellino Amarullah, Rendy Ampu Syura Ananda Wijaya Andreas Andreas Andreas Danny Agus W Andreas Saputra Andrian Wijaya Angel Kelly Asyraq, Cerwyn Bakti Ananda Fernando Bautista, Christian Bebin Paula Bella Jenni Ourelia Boy Putra Brilliant Chandra Pratama Calvin Bertnas Valentino Calvin Saputra Carissa Maharani Chandra Chandra Saputra Christian Richie Wijaya Clara Meyhazlinda Putri Clement, Michael Joy Daffa Yudha Musyaffa Daniel Daniel Daniel Johan Daniel Udjulawa Daniel Wijaya Darwin Saputra David Sebastian Dedy Hermanto Desta Rahman Theja Desy Iba Ricoida Dicky Ryanto Fernandes Dina Lestari Putri Diva Putri Kynta Dwi Apriyanti Sastika Dwi Cahyadi, Ambrosius Effendi pratama, Samuel Egi Fransisco Saputra Eka Puji Widiyanto Evangs Mailoa Evi Maria Fadhel Muhammad Fadhil Sa'adat Farisi, Ahmad Farisi, Ahmad Fathimah Azzahra Felicia Felicia Felix Gunawan Fellyca Effendi Fellycia Caroline Femmy Johan Feriyanto Feriyanto Ferliansyah, Fernando Fernandi Indi Nizar G Fernando Feliansyah Fernando Fernando Fernando Namas Fionna Caroline Florence Renaldo Frans Bachtiar Fransiskus Daniel Chandra Frisky Wijaya Genisshanda Nabila Matari Geraldo Wilson Gerry Christian Pilipus Gunawan, Michael Hafidz Irsyad Hafiz Irsyad Hafizh Pebrian Hansen Hansen Hendrawan, Malvin Hendry Hindriyanto Dwi Purnomo Ilham Indra Hidayat Imelia Dwinora Cahyati Indi Nizar G, Fernandi Ivan Luthfi Laksono Ivan Luthfi Laksono Jackie Wijaya Jasen Jonathan Jaysen Stephanus Ja`Far Ja`Far Jelvin Krisna Putra Jennifer Verty Jerin, Nathaniel Jesen Ong Jonathan Jason Constantine Jonathan Tanujaya Jonathan Wijaya Joseph Eduard Uly Loni Jovansa Putra Laksana Kasanova, Sinyo Kelvin Dwi Wahyudi Kevin agustria zahri Kevin Andreas KGS M Ammar Yazid Klaudius Audie Irsansaputra Kurniawan, Ricky Arie Laurentius Ricardo Wijaya Leo Chandra Leonardo Yahya Liem, Steven Lin, Valen Julyo Armando Davincy Lipi Amanda Putra Lucretia, Jolyn M Lazuardi Ferdillian M. Dhafa Adjie Saputra Marcelino Marcelino Mario Rivaldo Michael Michael Joy Clement michael Wijaya Migel Orvin Febryan Millenia Mudita Chandra Muhammad Abdul Azizul Hakim Muhammad Alfa Rizi Muhammad Azril Fahrezi Muhammad Dafhi Mayrizkiy Muhammad Dody Muhammad Fadli Muhammad Fajar Ariansyah Muhammad Hamdandi Muhammad Naufal Anugrah Muhammad Radja Juang Jamemiko Muhammad Redho Saputra Muhammad Reyza Nirwana Muhammad Robi, Muhammad Muhammad Tri Setianto Nabila Syiva Altarisa Nabilah Dayanah Nathacia Lais Naufal Akbar Neilsen Nicholas Komah Nicolas Jacky Pratama Hasan Nova Ariansyah Opita Purwasih Pambudi, Readysna Krisna Peter Reynard Susanto Pibriana, Desi Prasetyo, Zavier Billy Pratama, Brilliant Chandra Putra Laksana, Jovansa Putri, Agnes Anastasia Raphael Lee Regian batistuta, Putra Reza Satria Rika Maulina Riki Chandra Rio Ferdynand Riska Fajriati Rivaldo Therino Elevan Rivaldo, Mario Riza Umami Rizky Kurniawan Rizvi Roshan, Muhamad Roby Julian Romi Laxi Ronaldo Putra Rusbandi rusbandi rusbandi, rusbandi Safeti Intan Pratiwi Salwa Fakhira Imletta San Gabriel Vanness Kenrick Erwi Sanila Maharani Santoso, Fian Julio Saputra Edika, Nelson Sardika, Ricky Putra Se, Abd Rosyiid Serenity Devina Suryanto Setiawan, Thomas Shela, Shela Sherdian Djunaidi Sinshevan Viswanatan Kravizt Erwi Siska Amelia Siti Fatimah Az Zahrah Sonia Sonia Sri Yulianto Joko Prasetyo Steffanie Angelica Stephanie Stephanie Stephen Setyawan Steven Tribethran Suparto, Adrian Suryasatria Trihadaru Sutarto Wijono Syahrani Nur Hakim Syalsabilla Valentisyesa Syifa Wahyuni Tad Gonsalves Tangguh Prana Welas Sukma Vannes Wijaya Vanness Bee Victoria Valensita Robert Vincent Vincent Virgiansyah, Muhammad Rifqi Wijang Widhiarso Wijang Widhiarso Wijaya, Ananda Wilcent, Wilcent William Wijaya Yennica Valentine Hagunawan Yohanes Andika Dharma Yohanes Fransisco Mardi Chandra Yohannes, Yohannes Yoko Saputra Dewa Yosefa Camilia Moniung Yunarto Yunarto, Yunarto `Adelia Anjelina