As optical systems advance in capability, they present new engineering challenges. This work focuses on two such challenges: controlling stray light in imaging systems with increasingly demanding out-of-field stray light requirements and understanding the rela…
Machine learning models deployed in tactical environments rely on high-quality labeled datasets, which are often challenging, expensive, and time-consuming to obtain. In addition, formal techniques for assuring model performance under dynamic conditions remain…
Brain tumors are life-threatening conditions that require accurate and timely diagnosis. In clinical practice, diagnosis is commonly performed through Magnetic Resonance Imaging (MRI) analysis by medical experts, which is time-consuming and subject to variabil…
The widespread adoption of deep learning has led to a surge in demand for the efficient deployment of Deep Neural Networks (DNNs) on embedded and resource-constrained systems. These platforms are increasingly tasked with performing complex inference workloads…
The continuous growth of machine learning methods has driven significant advances in areas such as natural language processing and computer vision. However, the performance of these models heavily depends on the quantity and quality of labeled data available f…
As the capabilities of Machine Learning models grow, so does the cost of power consumption and time. In the era of deep learning, models have become larger and larger. While the complexity of these models leads to greater performance, they also require more co…
A fundamental challenge in the realm of computer vision lies in accurately modeling/characterizing image distributions. For example, in high-level vision tasks, better representations of images in the latent space can significantly enhance downstream processes…
Quantization has become a key approach for reducing storage and computational demands of deep neural networks while maintaining high accuracy. Although 8-bit quantization is well-established for convolutional architectures such as ResNet50 and MobileNetV2, its…
Modern datasets are increasingly high-dimensional and multiway, naturally represented as tensors with multiple indexed variables. Such data arise in numerous applications, including multivariate time series forecasting, 3D medical imaging, and climate modeling…
As the demand for renewable energy sources increases, the vulnerability of solar panels to lightning strikes becomes a critical concern. This research explores the correlation between lightning-induced voltage fluctuations and the resultant damage intensity on…
This Master’s thesis investigates a deep learning–based approach for accurate detection of COVID-19 from chest X-ray (CXR) images using Convolutional Neural Networks (CNNs). Accurate and timely identification of COVID-19 cases from radiographic images is essen…
In the field of Computer Vision (CV), the pursuit of human-level recognition and reasoning of visual scenes has been a long-standing aspiration. Over the past decade, significant contributions to the progress of CV have been made by deep learning, facilitated…
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.
