Sökning: "mobil nätverk"

Visar resultat 1 - 5 av 69 uppsatser innehållade orden mobil nätverk.

1. 1. Velocity Control of a Mobile Charger in a Wireless Rechargeable Sensor Network

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Emilia Haltorp; [2023]
   Nyckelord :Wireless Sensor Networks; Mobile Charger; Wireless Energy Transfer; Traveling Salesman Problem; Trådlösa Sensornätverk; Mobil laddare; Trådlös strömöverföring; Handelsresandeprobleme;

   Sammanfattning : Wireless sensor networks (WSN) are one of the most rapidly evolving technical areas right now. They can be used in a lot of different applications, environmental monitoring and health applications being two examples. The sensors can be placed in hazardous and remote environments since there is no need for cabling or manual maintenance. LÄS MER

3. 2. Multi-Scale Task Dynamics in Transfer and Multi-Task Learning : Towards Efficient Perception for Autonomous Driving

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Simon Ekman von Huth; [2023]
   Nyckelord :Autonomous Driving; Computer Vision; Deep Learning; Machine Learning; Multi-Task Learning; Transfer Learning; Task Relationships; Task Dynamics; Python; Multi-Scale Representation Learning; Fuss-Free Network; Självkörande Fordon; Datorseende; Djupinlärning; Maskininlärning; Multiuppgiftsinlärning; Överföringsinlärning; Uppgiftsrelationer; Uppgiftsdynamik; Python; Flerskalig Representationsinlärning; Fuss-Free Nätverk;

   Sammanfattning : Autonomous driving technology has the potential to revolutionize the way we think about transportation and its impact on society. Perceiving the environment is a key aspect of autonomous driving, which involves multiple computer vision tasks. LÄS MER

4. 3. Deep Reinforcement Learning on Social Environment Aware Navigation based on Maps

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Victor Sanchez; [2023]
   Nyckelord :Deep Reinforcement Learning; Environment-aware navigation; Robotics; Artificial Intelligence; Apprentissage par renforcement profond; Navigation consciente de l’humain; Intelligence Artificielle; Robotique; Djup Förstärkande Inlärning; Människomedveten navigering; Robotik; Artificiell Intelligens;

   Sammanfattning : Reinforcement learning (RL) has seen a fast expansion in recent years of its successful application to a range of decision-making and complex control tasks. Moreover, deep learning offers RL the opportunity to enlarge its spectrum of complex fields. LÄS MER

5. 4. Unsupervised Domain Adaptation for 3D Object Detection Using Adversarial Adaptation : Learning Transferable LiDAR Features for a Delivery Robot

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Mattias Hansson; [2023]
   Nyckelord :Unsupervised Domain Adaptation; 3D Object Detection; Mobile Robotics; Adversarial Adaptation; Computer Vision; Oövervakad Domänanpassning; 3D Objektigenkänning; Mobila Robotar; Motspelaranpassning; Datorseende;

   Sammanfattning : 3D object detection is the task of detecting the full 3D pose of objects relative to an autonomous platform. It is an important perception system that can be used to plan actions according to the behavior of other dynamic objects in an environment. LÄS MER

7. 5. Performance Evaluation of Kotlin Multiplatform Mobile and Native iOS Development in Swift

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Anna Skantz; [2023]
   Nyckelord :Kotlin Multiplatform Mobile; Cross-platform; Native; iOS; Kotlin; Swift; Performance Evaluation; Benchmarking; Mobile; Garbage Collection; Kotlin Multiplatform Mobile; Plattformsoberoende; Native; iOS; Kotlin; Swift; Prestandautvärdering; Benchmarking; Mobil; Garbage Collection;

   Sammanfattning : Today's mobile development resides in the two main operating systems Android and iOS. It is popular to develop mobile applications individually for each respective platform, referred to as native development. To reduce additional costs, cross-platform solutions have emerged that enable shared development for both platforms. LÄS MER