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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) SITEKIN: Jurnal Sains, Teknologi dan Industri Seminar Nasional Informatika (SEMNASIF) JOIV : International Journal on Informatics Visualization SENTIA 2016 Jurnal Pengabdian Polinema Kepada Masyarakat International Journal of Multidisciplinary: Applied Business and Education Research JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Kepada Masyarakat Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal Ilmiah Edutic : Pendidikan dan Informatika International Journal of Health, Engineering and Technology Jurnal Informatika Polinema (JIP) Jurnal Pengabdian Kepada Masyarakat
Astiningrum, Mungki
Teknik Informatika, Teknologi Informasi, Politeknik Negeri Malang
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Journal : JOIV : International Journal on Informatics Visualization

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An Experimental Study on Deep Learning Technique Implemented on Low Specification OpenMV Cam H7 Device Asmara, Rosa Andrie; Rosiani, Ulla Delfana; Mentari, Mustika; Syulistyo, Arie Rachmad; Shoumi, Milyun Ni'ma; Astiningrum, Mungki
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2299

Abstract

This research aims to identify and recognize the OpenMV Camera H7. In this research, all tests were carried out using Deep Machine Learning and applied to several functions, including Face Recognition, Facial Expression Recognition, Detection and Calculation of the Number of Objects, and Object Depth Estimation. Face Expression Recognition was used in the Convolutional Neural Network to recognize five facial expressions: angry, happy, neutral, sad, and surprised. This allowed the use of a primary dataset with a 48MP resolution camera. Some scenarios are prepared to meet environment variability in the implementation, such as indoor and outdoor environments, with different lighting and distance. Most pre-trained models in each identification or recognition used mobileNetV2 since this model allows low computation cost and matches with low hardware specifications. The object detection and counting module compared two methods: the conventional Haar Cascade and the Deep Learning MobileNetV2 model. The training and validation process is not recommended to be carried out on OpenMV devices but on computers with high specifications. This research was trained and validated using selected primary and secondary data, with 1500 image data. The computing time required is around 5 minutes for ten epochs. On average, recognition results on OpenMV devices take around 0.3 - 2 seconds for each frame. The accuracy of the recognition results varies depending on the pre-trained model and the dataset used, but overall, the accuracy levels achieved tend to be very high, exceeding 96.6%.
Co-Authors Abdul Muhsyi Ade Putra Lesmana Adhitya Bhawiyuga, Adhitya Adittiyaputra, Diva Agung Nugroho Pramudhita Aldodhery, Zigrozora Krishy Amien, Moch Ma’ruf Amrozi, Aris Nur Annisa Puspa Kirana Ari Zanupratama Arie Rachmad Syulistyo Arif, Rizqya Zakyyatul Asyraq, Farhan Azharuddin Atiqah Nurul Asri Aulia Rachmannisa Diwantari Aura Kanza Caesaria Azkia Nury Farizah Batubulan, Kadek Suarjuna Budi Harijanto, Budi Candra Bella Vista Cecilia, Sintia Dardanela Denny Nur Ramadhan Dhebys Suryani Hormansyah Dhebys Suryani Hormansyah, Dhebys Suryani Dhike Almira Ramadiyah Dian Hanifudin Subhi Dika Rizky Yunianto Dinda, Elistya Rahma Diva Adittiyaputra Dwi Puspitasari Dwi Puspitasari DWI PUSPITASARI Dyah Ayu Irawati Dyah Ayu Irawati Dyah Ayu Irawati, Dyah Ayu DyahAyu Irawati Elistya Rahma Dinda Elly Fatmawati Elly Fatmawati, Elly Erfan Rohadi Excellina Excellina Excellina, Excellina Faisal Rahutomo Farhan Azharuddin Asyraq Farizah, Azkia Nury Gunawan Budi Prasetyo Ika Dyah Rahmawati Ika Kusumaning Putri Ilmi, Muhammad Fikrul Indra Dharma Wijaya Indra Dharma Wijaya, Indra Dharma Irawati, DyahAyu Lesmana, Ade Putra M. Alfin Zakariya Maya Shoburu Rohmah Moch Ma’ruf Amien Moch Zawaruddin Abdullah Muhammad Fikrul Ilmi Mustika Mentari Nabilla Aqmarina Ariditya Pambudi, Sandy Priyo Pramana Yoga Saputra Putra Prima Arhandi, Putra Prima Rahmad, Cahya Ramadiyah, Dhike Almira Rawansyah Rawansyah Rawansyah, Rawansyah Rentia Ayu Suprapto Ridwan Rismanto Rifa'i, Bahtiar Rizqya Zakyyatul Arif Rohmah, Maya Shoburu Rokhimatul Wakhidah Rosa Andrie Asmara Sandy Priyo Pambudi Setiadi, Chandrasena Shoumi, Milyun Ni’ma Sintia Dardanela Cecilia Siti Nuraisyah Sultan Achmad Qum Masykuro Nur Santiko Suprapto, Rentia Ayu Toga Aldila Cinderatama Ulla Delfana Rosiani Vivi Nur Wijayaningrum Yan Watequlis Syaifudin Yoppy Yunhasnawa Yuri Arianto Yuri Ariyanto Yuri Ariyanto Yuri Ariyanto Yushintia Pramitarini Zakariya, M. Alfin Zanupratama, Ari Zigrozora Krishy Aldodhery