KLASIFIKASI FRAKTUR TULANG PADA CITRA RONTGEN MENGGUNAKAN METODE CANNY EDGE D…

Fractures in bones are a common occurrence in the medical field. Accidents are the leading cause of such injuries in Indonesia, particularly among children and males. Currently, fracture identification through X-ray images is performed using conventional methods that rely on visual analysis by doctors, which are often inaccurate. This study proposes the use of Convolutional Neural Network (CNN)…

SEGMENTASI PEMBULUH DARAH PADA CITRA RETINA MENGGUNAKAN ARSITEKTUR RESVNET

The use of retinal images on the eye fundus is becoming an important tool in the medical world, especially for the diagnosis of eye diseases. Segmentation of blood vessels in retinal images is one of the important steps in medical analysis to detect and diagnose various eye diseases, such as diabetic retinopathy, glaucoma, and macular degeneration. Using the ResVNet method, segmentation is perf…

PERBAIKAN KUALITAS CITRA JANTUNG MENGGUNAKAN METODE DEEP LEARNING

In infant heart ultrasound images, problems often appear such as low brightness, noise and blur. To overcome this problem, an improvement process is needed using deep learning techniques such as MIRNet, Autoencoder, EDR-CNNs, and LLCNN. The best method is MIRNet, which produces PSNR values of 36.37 dB, MSE of 16.69, and SSIM of 92.86. In addition, the results obtained were tested through classi…

PERANCANGAN YOU ONLY LOOK ONCE (YOLO) DENGAN SLICING AIDED HYPER INFERENCE (S…

Pengenalan objek berukuran kecil merupakan tantangan signifikan dalam tugas deteksi dan segmentasi model, terutama ketika objek tersebut sangat kecil dibandingkan dengan area sekitarnya. Hal ini sangat penting dalam aplikasi seperti diagnosis penyakit, yang memerlukan presisi tinggi. Tantangan ini semakin kompleks dengan adanya variasi orientasi citra, tingkat noise yang tinggi, kompleksitas la…

SEGMENTASI CITRA JANTUNG ANAK MENGGUNAKAN METODE YOLO

Child heart image segmentation is a crucial step in medical analysis for the diagnosis of heart diseases. In this study, we utilize the You Only Look Once (YOLO) method for the segmentation of child heart images. YOLO is a well known deep learning model in object detection due to its ability to perform real time detection with high accuracy. We collected a dataset of child heart images, perform…

PENINGKATAN KUALITAS UNTUK DETEKSI OBJEK PADA CITRA SATELIT MENGGUNAKAN METOD…

Satellite images are images or photos taken from satellites that revolve around the Earth, where the image is used in the fields of mapping, meteorology and environmental monitoring. However, there is a problem that the images produced by these satellites sometimes have low resolution and the objects in the image are not clearly visible. Therefore, to overcome these problems, an increase in res…

SEGMENTASI DAN KLASIFIKASI TINGKAT KEPARAHAN LESI PRA KANKER SERVIKS DENGAN M…

Seiring berkembangnya teknologi, model deep learning kini dapat digunakan untuk mengimplementasikan proses segmentasi dan klasifikasi citra. Penelitian ini bertujuan untuk mengembangkan model segmentasi dan klasifikasi kanker serviks menggunakan arsitektur U-Net Convolutional Neural Network (CNN). Model U-Net dikembangkan untuk melakukan segmentasi jaringan serviks dan memisahkan area yang menc…

RANCANG BANGUN SISTEM DETEKSI PERMUKAAN KOTAK PADA SIMULATOR ROV (REMOTELY OP…

In recent decades, the use of Remotely Operated Vehicles (ROVs) has significantly increased in various underwater applications, such as exploration, structural inspection, and rescue operations. One of the main challenges is the ROV's ability to detect and map objects in its surroundings. This project aims to develop a relevant ROV simulator for detecting environmental and industrial underwater…

DETEKSI TUMOR OTAK PADA CITRA DIGITAL MRI MENGGUNAKAN METODE FASTER REGION-BA…

This research evaluates the performance of several Faster R-CNN models with different hyperparameter configurations for brain tumor detection tasks. Evaluation results show that Model with a learning rate of 0.01, batch size of 4, Resnet50 backbone, and a dataset ratio of 80:20, achieved the best results. This model achieved mAP at IoU thresholds of 0.3, 0.4, and 0.5 of 0.9503, 0.9377, and 0.89…

ROBOT VISI

Edition

1

ISBN/ISSN

978-979-756-469-8

Collation

x + 150 hlm, 1 Jil.; 21 cm

Series Title

-

Call Number

006.3 Fad r