The rapid increase in data generated by edge devices and IoT technologies demands efficient management solutions, especially in terms of cost and infrastructure. Key challenges include expensive data labeling, requiring significant human resources, and ensurin…
In the field of computer vision, deep learning has demonstrated remarkable accomplishments. However, the dependence on extensive annotated datasets poses significant challenges, particularly when such data is scarce, costly, or ethically sensitive. This thesis…
It is the aim of this paper to find out how brain MRI image classification accuracy can be improved through a new hybrid deep learning model that incorporates Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), U-Net, ResNet, and GoogleNet. G…
Vers un apprentissage avec peu d’annotations en vision par ordinateur : Application à la classification et à la détection d’objets dans les images Nous développons dans cette thèse des contributions théoriques, algorithmiques et expérimentales pour l’apprentis…
Historical manuscripts embody important witnesses of cultural heritage.In recent years, libraries all over the world have scanned voluminous document collections and often made the scanned page images available online.However, especially for handwritten manusc…
Machine Learning (ML) systems such as Convolutional Neural Networks (CNNs) are susceptible to adversarial scenarios. In these scenarios, an attacker attempts to manipulate or deceive a machine learning model by providing malicious input resulting in incorrect…
As machine learning grows more prevalent in the medical field, it is important to ensure that fairness is considered as a central criterion in the evaluation of algorithms and models. Building upon previous work, we study a set of machine learning models used…
Convolutional neural networks (CNNs) are a well-established technique for image classification problems. While the topology of a CNN strongly affects the performance of that CNN, designing a CNN’s topology remains a difficult task, often with nothing better th…
From the beginning of this century, Artificial Intelligence (AI) has evolved to handle problems in image recognition, classification, segmentation, etc. AI learning is categorized by supervised, semi-supervised, unsupervised or reinforcement learning. Some res…
Machine learning methods have recently increased in appearance in navigation and guidance applications by means of image classification. This thesis sought to advance the ongoing Electrical and Computer Engineering (ECE) Control Systems and Robotics Laboratory…
Spiking neural networks are biologically plausible counterparts of artificial neural networks. Artificial neural networks are usually trained with stochastic gradient descent (SGD) and spiking neural networks are trained with bioinspired spike timing dependent…
Optical Character Recognition (OCR) is one of the central problems in pattern recognition. Its applications have played a great role in the digitization of document images collected from het- erogeneous sources. Many of the well-known scripts have OCR systems…
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.
