Amin Nur Ambarwati
Analisis performa metode convolutional neural network (CNN) pada fungsi aktivasi ReLU dan mish dalam mendeteksi penyakit katarak pada data citra fundus = Performance analysis of convolutional neural network (CNN) methods with ReLU and mish activation functions in detecting cataract disease in fundus image.
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2021
 UI - Skripsi Membership
Rizka Amalia
Computer Aided Diagnosis Berbasis Convolutional Neural Network dan Long Short-Term Memory untuk Pendeteksian dan Captioning Retinopati Diabetik = Computer Aided Diagnosis Based on Convolutional Neural Network and Long Short-Term Memory for Diabetic Retinopathy Detection and Captioning
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2021
 UI - Tesis Membership
Amnia Salma
Implementasi attention mechanism pada pembangunan architecture convolutional neural network untuk deteksi penyakit retinopati diabetik melalui gambar fundus = Implementation of attention mechanism in convolutional neural network architecture development for diabetic retinopathy detection through fundus image.
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2021
 UI - Tesis Membership
Hans Kristian
Analisis Kinerja Algoritma Image Generator for Tabular Data dan Model Convolutional Neural Networks dalam Memprediksi Fraud Asuransi = Performance Analysis of Image Generator for Tabular Data Algorithm and Convolutional Neural Networks Model to Predict Insurance Fraud
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2023
 UI - Skripsi Membership
Saragih, Glori Stephani
Merancang Metode Klasifikasi Stroke Iskemik Berdasarkan Output dari Proses Ekstraksi Citra CT Scan pada Convolutional Neural Networks dengan Beberapa Model Machine Learning = Ischemic Stroke Classification using Several Machine Learning Methods Based on Feature Extraction of Convolutional Neural Networks
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2021
 UI - Tesis Membership