Sökning: "Resursbegränsade system"

Visar resultat 1 - 5 av 21 uppsatser innehållade orden Resursbegränsade system.

  1. 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)

    Författare :Xinchen Wang; [2024]
    Nyckelord :Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

    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

  3. 2. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network

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

    Författare :Jiayi Feng; [2023]
    Nyckelord :DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Embedded Systems; DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Inbyggda system;

    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

  4. 3. Towards Adaptive Image Resolution for Visual SLAM on Resource-constrained Devices

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

    Författare :Herman Blenneros; [2023]
    Nyckelord :Visual localization and mapping; Runtime-control; Resource-constrained devices; Bildbaserad lokalisering och kartläggning; Realtidsreglering; Resursbegränsade enheter;

    Sammanfattning : Today, a large number of devices with small form factors and limited resources are being integrated with processes to perform complex tasks such as localization and mapping. One example of this are headsets used for Extended Reality. LÄS MER

  5. 4. Outlier Robustness in Server-Assisted Collaborative SLAM : Evaluating Outlier Impact and Improving Robustness

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

    Författare :José Miguel de Almeida Pedro; [2023]
    Nyckelord :SLAM; Robust Estimation; Multi-Device Algorithms; SLAM; Robust uppskattning; Algoritmer för flera enheter;

    Sammanfattning : In order to be able to perform many tasks, autonomous devices need to understand their environment and know where they are in this environment. Simultaneous Localisation and Mapping (SLAM) is a solution to this problem. LÄS MER

  7. 5. Computation Offloading for Real-Time Applications : Server Time Reservation for Periodic Tasks

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

    Författare :Lizzy Tengana Hurtado; [2023]
    Nyckelord :Computation Offloading; Real-Time Applications; Resource Reservation; Beräkningsavlastning; realtidsapplikationer; resursreservation;

    Sammanfattning : Edge computing is a distributed computing paradigm where computing resources are located physically closer to the data source compared to the traditional cloud computing paradigm. Edge computing enables computation offloading from resource-constrained devices to more powerful servers in the edge and cloud. LÄS MER