Sökning: "resource-constrained systems"

Visar resultat 1 - 5 av 31 uppsatser innehållade orden resource-constrained systems.

  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. ANOMALY DETECTION FOR INDUSTRIAL APPLICATIONS USING COMMODITY HARDWARE

    Kandidat-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :John Moberg; Jonathan Widén; [2023]
    Nyckelord :Computer Vision; Anomaly Detection; Single Board Computer; Embedded systems;

    Sammanfattning : As the Automotive industry is heavily regulated from a quality point of view, excellence in pro-duction is obligatory. Due to the fact that removing human error from humans is impossible, new solutions must be found. 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. Evaluating Thread network performance, locating and strengthening weak radio links

    Master-uppsats, Linköpings universitet/Fysik, elektroteknik och matematik; Linköpings universitet/Tekniska fakulteten

    Författare :André du Rietz; Elias Salo; [2023]
    Nyckelord :Internet of Things; IoT; Thread network; Evaluating Thread Network;

    Sammanfattning : In the fast-developing world we are living in, a tech phenomenon known as the Internet of Things (IoT) has taken hold. It has seen a lot of development over the past few decades, and today there are an estimated 30 billion IoT devices active. IoT is a machine-to-machine network that senses the world with the help of sensors. LÄS MER

  7. 5. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

    Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER