Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Jurnal Teknologi dan Sistem Komputer

Deteksi Arteri Karotis pada Citra Ultrasound B-Mode Berbasis Convolution Neural Network Single Shot Multibox Detector I Made Gede Sunarya; Tita Karlita; Joko Priambodo; Rika Rokhana; Eko Mulyanto Yuniarno; Tri Arief Sardjono; Ismoyo Sunu; I Ketut Eddy Purnama
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 2, Year 2019 (April 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1288.438 KB) | DOI: 10.14710/jtsiskom.7.2.2019.56-63

Abstract

Detection of vascular areas (blood vessels) using B-Mode ultrasound images is needed for automatic applications such as registration and navigation in medical operations. This study developed the detection of the carotid artery area using Convolution Neural Network Single Shot Network Multibox Detector (SSD) to determine the bounding box ROI of the carotid artery area in B-mode ultrasound images. The data used are B-Mode ultrasound images on the neck that contain the carotid artery area (primary data). SSD method result is 95% of accuracy which is higher than the Hough transformation method, Ellipse method, and Faster RCNN in detecting carotid artery area in the B-Mode ultrasound image. The use of image enhancement with Gaussian filter, histogram equalization, and Median filters in this method can increase detection accuracy. The best process time of the proposed method is 2.09 seconds so that it can be applied in a real-time system.
Paralel Spatial Pyramid Convolutional Neural Network untuk Verifikasi Kekerabatan berbasis Citra Wajah Reza Fuad Rachmadi; I Ketut Eddy Purnama
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 4, Year 2018 (October 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.288 KB) | DOI: 10.14710/jtsiskom.6.4.2018.152-157

Abstract

In this paper, we proposed a parallel spatial pyramid CNN classifier for image-based kinship verification problem. Two face images that compared for kinship verification treated as input for each parallel convolutional network of our classifier. Each parallel convolutional network constructed using spatial pyramid CNN classifier. At the end of the convolutional network, we use three fully connected layers to combine each spatial pyramid CNN features and decided the final kinship prediction. We tested the proposed classifier using large-scale kinship verification dataset, called FIW dataset, consists of seven kinship problems from 1,000 families. In our approach, we treated each kinship problem as a binary classification problem with two output. We train our classifier separately for each kinship problem with same training configuration. Overall, our proposed method can achieve an average accuracy of more than 60% and outperform the baseline method.
Klasifikasi Citra Satelit menggunakan Lightweight Ensemble Convolutional Network Rachmadi, Reza Fuad; Prioko, Kentani Langgalih; Nugroho, Supeno Mardi Susiki; Purnama, I Ketut Eddy
Jurnal Teknologi dan Sistem Komputer [IN PRESS] Volume 10, Issue 3, Year 2022 (July 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14346

Abstract

Citra satelit dapat digunakan salah satunya sebagai pengamatan kondisi atmosfer dan permukaan pada bumi. Dengan semakin berkembangnya teknologi citra satelit, waktu untuk pengambilan citra satelit menjadi lebih efisien. Makalah ini melakukan eksperimen menggunakan klasifier ensemble convolutional network untuk melakukan pengenalan kondisi atmosfer pada citra satelit. Empat buah arsitektur Convolutional Neural Network (CNN) digunakan dalam eksperimen ini, yaitu MobileNetV2, ResNet18, ResNet18Half, dan SqueezeNet. Keempat arsitektur CNN tersebut dipilih karena mempunyai jumlah parameter yang tidak terlalu besar (lightweight) serta dapat diterapkan pada banyak perangkat keras tertanam. Eksperimen yang dilakukan dengan menggunakan dataset USTC SmokeRS memperlihatkan bahwa klasifier ensemble memperoleh hasil yang baik dengan akurasi rata-rata tertinggi sebesar 97.06 %.
Co-Authors Abd Rahman Adhi Dharma Wibawa Adi Sutanto Ahmad Zaini Ahsan Ahsan Ait-Souar, Iliès Alamsyah Alamsyah - Alamsyah Alamsyah Andi Kurniawan Nugroho Arham Arham, Arham Arina Qona'ah Asayanda, Fikra Agha Rabbani Bernaridho Hutabarat, Bernaridho Boedinugroho, Hanny Budi Nur Iman Budi Santoso Catur Supriyanto Chastine Fatichah Dian Ratnawati Diana Purwitasari Dinar Mutiara Kusumo Nugraheni Effendy Hadi Sutanto Eka Dwi Nurcahya Eko Mulyanto Yuniarno Eko Mulyanto Yuniarno Elly Purwantini Endang Sri Rahayu Esther Irawati Setiawan Filiazsanti, Almira Firman Arifin Gijsbertus Jacob Verkerke Gijsbertus Jacob Verkerke Guruh Fajar Shidik Gusmaniarti, Gusmaniarti Handayeni, Ketut Dewi Martha Erli Hartarto Junaedi Hermawan, Norma Hernanda, Arta Kusuma Hidayat Arifin I Made Gede Sunarya Ida Hastuti Ima Kurniastuti Iman Fahruzi Ingrid Nurtanio Ismoyo Sunu Isturom Arif Jaya Pranata, Jaya Joko Priambodo Juanita, Safitri Khakim Ghozali Kristian, Yosi Kurniawan, Arief Lilik Anifah Lukman Affandhy Lukman Zaman Margareta Rinastiti Masy Ari Ulinuha Mauridhi Heri Purnomo Mauridhi Heri Purnomo Mauridhi Hery Purnomo Mauridhi Hery Purnomo Mira Candra Kirana Moch Hariadi Moch Hariadi Mochamad Hariadi Mochamad Yusuf Alsagaff Mochammad Hariadi Muhammad Anshari Muhammad Hariadi Muhtadin Muhtadin Muhtadin Mulyanto, Eko Munawir . Munawir Munawir Munir, M Syahrul Myrtati Dyah Artaria Nazarrudin, Ahmad Ricky Nofiandri Setyasmara Nursalam . Pramunanto, Eko Priambodo, Joko Prioko, Kentani Langgalih Pulung Nurtantio Andono Putu Gde Ariastita Putu Hendra Suputra R Dimas Adityo Rachmadi, Reza Fuad Raihan, Muhammad Reza Fuad Rachmadi Ricardus Anggi Pramunendar Rifky Octavia Pradipta Rika Rokhana Rika Rokhana Rima Tri Wahyuningrum Rima Tri Wahyuningrum Robby Aldriyanto Raffly Rokhana, Rika Rumala, Dewinda Julianensi Saiful Bukhori Saiful Bukhori Sensusiati, Anggraini Dwi Setijadi, Eko Slamet Hartono Stevanus Hardiristanto Stevanus Hardiristanto Stevanus Hardiristanto, Stevanus Sugiyanto - Supeno Mardi Susiki Nugroho, Supeno Mardi Suryo, Yoedo Ageng Terawan Agus Putranto Tita Karlita Tita Karlita Tita Karlita Tomoko Hasegawa Tri Arief Sardjono Wulandari, Ariani Dwi Yosi Kristian Yulis Setiya Dewi Zaimah Permatasari Zaman, Lukman