Sökning: "Autonomous driving systems"
Visar resultat 1 - 5 av 147 uppsatser innehållade orden Autonomous driving systems.
1. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER
2. Challenges in Specifying Safety-Critical Systems with AI-Components
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Safety is an important feature in automotive industry. Safety critical system such as Advanced Driver Assistance System (ADAS) and Autonomous Driving (AD) follows certain processes and procedures in order to perform the desired function safely. LÄS MER
3. On Systematically Exploring the State Space for Events with SFCs
Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : In the process of developing autonomous driving systems (AD systems), ensuring safety remains a constant and continuous priority. Scenario-based testing is a popular approach to guarantee the safety of AD systems, which however meets challenges in terms of diversity and efficiency of generation, as well as evaluating existing test case datasets in terms of their coverage of the different variations of a particular maneuver. LÄS MER
4. Systematically Analyzing Synthetic Automotive Data to support Space Filling Curves-based Maneuver Detection
Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Context: In autonomous driving system development, the identification of maneuvers within large datasets is progressively becoming more complex, primarily due to the inherent complexity arising from the multidimensional nature of the data describing these maneuvers. In this context, algorithms based on Space-Filling Curves can be an effective way to index datasets by creating a single-dimensional representation of the maneuvers. LÄS MER
5. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER