The goal of this thesis is to solve the significant problem of inter-observer variability-induced diagnostic delays by presenting a sophisticated deep learning system for automated brain tumor diagnosis utilizing MRI imagery. Pituitary adenoma, extra-axial men…
This thesis investigates the implementation of image denoising using Neural Networks (NN) in conjunction with wavelet transform techniques. For the purpose of data simulation, images are intentionally corrupted with additive white Gaussian noise (AWGN) at vari…
Penelitian ini dilatarbelakangi oleh masih rendahnya keterampilan menulis Bahasa Arab siswa kelas XI MAN 2 Yogyakarta, khususnya dalam menulis kalimat dan paragraf sederhana. Penelitian ini bertujuan untuk mengetahui pengaruh pendekatan deep learning berbasis…
Magnetic Resonance Imaging (MRI) is a vital non-invasive tool for high-resolution brain imaging, yet its long acquisition time frequently results in patient movement leading to motion artifacts, particularly among non-compliant patients like newborns. While De…
This research represents a hybrid model for polyp segmentation in medical images, which combines convolutional neural networks (CNN) and vision transformers (ViT). We propose a hybrid architecture that integrates UNet with a Vision Transformer, where UNet is u…
Computed tomography (CT) is widely used for the diagnosis and assessment of pulmonary and hepatic diseases because it provides detailed anatomical information.With the development of deep learning, CT image analysis has advanced significantly in segmentation,…
Generative artificial intelligence (AI) and its applications offer significant benefits but raise potentially critical societal and ethical concerns. This thesis explores the field of synthetic content generation and detection, with a particular focus on synth…
Large-scale pretraining has produced powerful deep learning representations, but real-world data rarely match the clean, uniform assumptions of standard transfer learning. This dissertation uses heterogeneous data to describe settings in which information diff…
Pneumonia is a leading global cause of mortality, claiming approximately 2.5 million lives an-nually and placing exceptional diagnostic pressure on radiologists in resource-limited settings. Manual interpretation of chest X-ray (CXR) images is time-consuming,…
Diagnosis of pneumonia from Chest X-Ray images holds a significant place in clinical practice due to its low cost and widespread availability. However, achieving high performance with deep learning-based methods generally requires a large amount of labeled dat…
This dissertation systematically studies the two core challenges faced by visual-language pretraining models (such as CLIP) in video action recognition tasks: insufficient temporal modeling and ambiguous semantic space. By constructing a temporal-enhanced mode…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
