Modern manufacturing is progressing towards Industry 4.0 and Robotics 4.0, which puts the industrial robots in the focus of contemporary manufacturing. These sophisticated robots keep on producing multi-sensor rich data, which depicts their internal kinematics…
Tato diplomová práce se zabývá využitím metod hlubokého učení pro sémantickou segmentaci leteckých snímků za účelem mapování průjezdnosti terénu pro mobilní roboty. Práce analyzuje současný stav poznání v oblasti hlubokých neuronových sítí a souvisejících dato…
Maneuver prediction is a critical component of decision-making in autonomous driving, particularly in complex urban environments where traffic participants continuously interact under uncertainty. Accurate and interpretable prediction of future driving maneuve…
Autonomous driving has progressed rapidly in recent years, driven largely by advances in machine learning, computer vision, and probabilistic optimization methods. Despite this progress, the deployment of autonomous systems in complex, safety-critical real- wo…
Autonomous driving in complex urban environments requires not only accurat e perception and prediction, but also strict adherence to physical constra ints and safety requirements.While recent deep learning approaches and Vi sion-Language-Action (VLA) models ha…
Advances in deep learning have revolutionized scene understanding in recent years, achieving unprecedented performance levels. As a result, nearly all autonomous vehicle perception systems now rely on learning-based Deep Neural Networks (DNNs). These methods a…
Autonomous driving systems rely heavily on sensor inputs to perceive and navigate their environment.However, individual sensors such as cameras or LiDAR often experience performance degradation in adverse weather conditions, which can lead to unreliable percep…
Reliable autonomous vehicle operation at urban intersections requires competence across the prediction–perception stack, yet current deep learning models underuse the structural priors that govern real-world driving. This thesis argues that incorporating struc…
Reinforcement Learning is a machine learning approach where the agent learns to make optimal decisions through trial and error, interacting with an environment to maximize cumulative reward. However, in safety critical domains like space exploration or autonom…
Modern wireless communication systems are increasingly required to operate under uncertain and heterogeneous conditions, spanning signal inference under unknown noise distributions, reliable transmission in the presence of adversarial interference, and adaptiv…
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.
