Objek Deteksi Makanan Khas Palembang Menggunakan  Algoritma YOLO (You Only Look Once)

Rahma, Lusiana; Syaputra, Hadi; Mirza, Ahmad Haidar; Purnamasari, Susan Dian

doi:10.47747/jurnalnik.v2i3.534

Cited by 17 publications

(15 citation statements)

References 3 publications

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“…Dataset yang sudah diunduh tidak hanya berupa gambar namun juga termasuk label gambar sesuai dengan jumlah gambar yang tersedia dengan format .txt yang akan digunakan untuk mengatur besar kecilnya objek dan rotasi yang dideteksinya [17]. Hasil dari proses pelatihan data akan menghasilkan beberapa parameter yaitu nilai recall, F1-score, rata-rata IoU, dan mAP.…”

Section: Alur Pengerjaan Datasetunclassified

Design and Build Vehicle Plate Detection System Using You Only Look Once Method Based on Android

Usen,

Hayat

2023

J. Tek. Inform. (JUTIF)

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The method of collecting the vehicle data is conducted conventionally by gathering data from each region to be converted into single, raw information in the form of vehicle plates for all regions, to be processed on a computer and sent to the Central Bureau of Statistics. It is then transformed into a form of national data file that provides information on vehicle plates for the Indonesian people. This kind of data gathering method requires a lot of time and effort. Therefore, it is a concern for researchers to detect vehicle plates using image processing by utilizing the Android-based You Only Look Once method. The YOLOv4 technique is used because it processes image data directly with optimal performance in order to produce faster predictions. In its application, the researchers use Google Collaboratory to create models and Android Studio for android applications. At the same time, the parameters studied were precision, recall, F1 score, average IoU, and mAP. By using the "Vehicle Registration Plate" dataset, the ratio of which is 70% in training data and 30% in data validation, an accuracy of 77% is obtained with a detection time of 0.05 seconds, whereas the average accuracy value is 86.82%. Therefore, it can be concluded that this study has an optimized performance for detecting vehicle plates using the Android application.

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Section: Alur Pengerjaan Datasetunclassified

Design and Build Vehicle Plate Detection System Using You Only Look Once Method Based on Android

Usen,

Hayat

2023

J. Tek. Inform. (JUTIF)

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“…Confusion matrix is a predictive analysis tool that displays and compares the actual value with the predicted model value. Prediction models that can be used to get the results of the evaluation matrix are Accuracy, Precision, Recall and F1 Score [19]. This confusion matrix is shown in Fig.…”

Section: F Confusion Matrixmentioning

confidence: 99%

Identification of Human Sperm based on Morphology Using the You Only Look Once Version 4 Algorithm

Aristoteles¹,

Syarif²,

Sutyarso³

et al. 2022

IJACSA

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Infertility is a crucial reproductive problem experienced by both men and women. Infertility is the inability to get pregnant within one year of sexual intercourse. This study focuses on infertility in men. Many causes that can cause infertility in men including sperm quality. Currently, identification of human sperm is still done manually by observing the sperm with the help of humans through a microscope, so it requires time and high costs. Therefore, high technology is needed to determine sperm quality in the form of deep learning technology based on video. Deep learning algorithms support this research in identifying human sperm cells. So deep learning can help detect sperm video automatically in the process of evaluating sperm cells to determine infertility. We use deep learning technology to identify sperm using the You Only Look Once version 4 (YOLOv4) algorithm. Purpose of this study was to analyze the level of accuracy of the YOLOv4 algorithm. The dataset used is sourced from a VISEM dataset of 85 videos. The results obtained are 90.31% AP (Average Precision) for sperm objects and 68.19% AP (Average Precision) for non-sperm objects, then for the results of the training obtained by the model 79.58% mAP (Mean Average Precision). Our research show result about identification of human sperm using YOLOv4. The results obtained by the YOLOv4 model can identify sperm and non-sperm objects. The output on the YOLOv4 model is able to identify objects in the test data in the form of video and image.

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“…Metode CNN merupakan suatu kelas pada neural network yang berspesialisasi dalam memproses data yang memiliki topologi seperti grid, misalnya gambar. Metode CNN dapat digunakan dalam pengenalan wajah, analisis dokumen, klasifikasi gambar, klasifikasi video, dsb [8].…”

Section: Metode Klasifikasiunclassified

Kinerja Algoritma Convolutional Neural Network dalam Klasifikasi Covid-19 Varian Omicron Berdasarkan Citra Ct-Scan Thoax

Nurdiawan

Herdiana²,

Ali³

et al. 2022

Jur. Ris. Kom.

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The second wave of the Covid-19 tsunami in India has broken the record for the highest number of additional cases and deaths in the world. Variant mutations are one of the contributing factors. Infection Crown variant Delta (B.1.617.2) is a mutation of the Covid-19 infection that has been endemic (SARS-CoV.2 B.1.617). The problem in this study is that the level of accuracy is still low in determining the covid-19 variant of the omicron resulting in uncertainty in decision makers by experts so that this research is needed to help with excellent accuracy measurements. The purpose of this study is to find a good model by applying the Convolutional Neural Network algorithm so that it can increase high accuracy and can be used in decision making by medical experts. The results of this study provide important information that the image size and the amount of input data greatly affect the level of accuracy in the Convolutional Neural Network method with the stages of data collection, preprocessing, Image Augmentation, Resize, Split Data, Convolutional Neural Network Architecture, Convolution, Pooling, Flattening, Full Connections, and Evaluations. Accuracy results with 400 input data produce training and testing (validation) on a chest x-ray image dataset using the Convolutional Neural Network architecture that has been created, 30 iterations (epochs) and 30 step_per_epochs showing an accuracy value of 0.88 or 88 % and the loss value is 0.3119 and the accuracy results with input data are 800 data, resulting in training and testing (validation) on the chest x-ray image dataset using the Convolutional Neural Network architecture that has been created, iterations (epochs) 30 times, and step_per_epoch as many as 30 shows an accuracy value of 0.93 or 93% and a loss value of 0.2711

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Objek Deteksi Makanan Khas Palembang Menggunakan Algoritma YOLO (You Only Look Once)

Cited by 17 publications

References 3 publications

Design and Build Vehicle Plate Detection System Using You Only Look Once Method Based on Android

Design and Build Vehicle Plate Detection System Using You Only Look Once Method Based on Android

Identification of Human Sperm based on Morphology Using the You Only Look Once Version 4 Algorithm

Kinerja Algoritma Convolutional Neural Network dalam Klasifikasi Covid-19 Varian Omicron Berdasarkan Citra Ct-Scan Thoax

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