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Found 5 from your keywords: subject="Model Deep Learning"
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ANALISIS KOMPARATIF MACHINE LEARNING DAN EXPLAINABLE ARTIFICIAL INTELLIGENCE …
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Febriani, Nabilla Suci

Traffic accidents are a road safety issue that can result in fatalities. This study aims to compare the performance of machine learning models namely, Random Forest, XGBoost and LightGBM and to explain the prediction results of the best model using the Explainable Artificial Intelligence (XAI) approach, with SHapley Additive exPlanations (SHAP) employed as the interpretation method. The data us…

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xiv, 98 hlm.; ilus.; tab.; 29 cm.
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Call Number
T2005642026
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EVALUASI METODE UNSUPERVISED LEARNING DALAM PENGELOMPOKAN DATA KECELAKAAN LAL…
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Junaidi, Khairunnisa

Traffic accidents are one of the transportation issues that require distribution analysis to identify areas with different accident characteristics. This study aims to compare the K-Means, DBSCAN, and Hierarchical Clustering methods in clustering traffic accident data based on geographical location and accident severity. The dataset used is derived from traffic accident data in the United Kingd…

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xvi, 109 hlm.; ilus.; tab.; 29 cm.
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Call Number
T2005732026
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PENINGKATAN KINERJA KLASIFIKASI GANGGUAN JANTUNG PADA SINYAL ELEKTROKARDIOGRA…
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Latifah, Siti

Electrocardiogram (ECG) signals represent the electrical activity of the heart and are used to record disorders such as arrhythmia and heart failure. Due to their non-stationary nature, ECG signals require a time-frequency domain approach to capture their dynamic characteristics more accurately. This study aims to develop and evaluate machine learning-based heart disorder classification models …

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xxvi, 229 hlm.; ilus.; tab.; 29 cm.
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Call Number
T2002302026
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MULTI OBJECT TRACKING PADA CITRA JANTUNG ANAK MENGGUNAKAN DEEP LEARNING
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Sya'bani, Muhammad Hanif

Congenital heart disease (CHD) in children, such as atrial septal defects (ASD), ventricular septal defects (VSD), and atrioventricular septal defects (AVSD), requires accurate diagnosis through dynamic analysis. However, existing methods for analyzing echocardiographic video are often limited to frame-by-frame analysis and are not yet capable of consistently tracking temporal changes. This stu…

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xv, 104 hlm.; ilus.; tab.; 29 cm.
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Call Number
T2002432026
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IMAGE CAPTIONING PADA CITRA SERVIKS UNTUK LAPORAN MEDIS BERBASIS MODEL DEEP L…
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Akrom, Ridwan

Image captioning is a task in the fields of computer vision (CV) and natural language processing (NLP) that aims to generate textual descriptions from an image. In this study, various combinations of encoder–decoder architectures were designed and evaluated to improve captioning performance on cervical medical images from the International Agency for Research on Cancer (IARC). The encoders us…

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ISBN/ISSN
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Collation
xiv, 99 hlm.; ilus.; tab.; 29 cm.
Series Title
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Call Number
T2001052026