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Showing result 1 - 5 of 11 essays matching the above criteria.

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

    University essay from KTH/Mekatronik och inbyggda styrsystem

    Author : Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Keywords : 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;

    Abstract : 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. READ MORE

  3. 2. Low-power Implementation of Neural Network Extension for RISC-V CPU

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Dario Lo Presti Costantino; [2023]
    Keywords : Artificial intelligence; Deep learning; Neural networks; Edge computing; Convolutional neural networks; Low-power electronics; RISC-V; AI accelerators; Parallel processing; Artificiell intelligens; Deep learning; Neurala nätverk; Edge computing; konvolutionella neurala nätverk; Lågeffektelektronik; RISC-V; AI-acceleratorer; Parallell bearbetning;

    Abstract : Deep Learning and Neural Networks have been studied and developed for many years as of today, but there is still a great need of research on this field, because the industry needs are rapidly changing. The new challenge in this field is called edge inference and it is the deployment of Deep Learning on small, simple and cheap devices, such as low-power microcontrollers. READ MORE

  4. 3. Evaluating The Performance of Machine Learning on Different Devices

    University essay from Mittuniversitetet/Institutionen för informationssystem och –teknologi

    Author : Robar Zangana; [2022]
    Keywords : IoT; Machine Learning; Tensorflow; Image classification; IoT; Maskininlärning; Tensorflow; Bildklassificering;

    Abstract : IoT-enheter blir allt populärare i takt med att de blir kraftfullare och skalbara. Därför var det viktigt att undersöka prestandan hos IoT-enheter när det kommer till maskininlärning. READ MORE

  5. 4. Evaluating the Performance of Machine Learning on Weak IoT devices

    University essay from Mittuniversitetet/Institutionen för informationssystem och –teknologi

    Author : Ahmad Alhalbi; [2022]
    Keywords : TinyML; Microcontrollers; Tersorflow; IoT; Maskininlärning ML ; TinyML; Mikrocontrollers; Tersorflow; IoT; Maskininlärning ML ;

    Abstract : TinyML är ett snabb växande tvärvetenskapligt område i maskininlärning. Den fokuserar på att möjliggöra maskininlärnings algoritmer på inbyggda enheter (mikrokontroller) som arbetar vid lågt effektområde. Syftet med denna studie är att analysera hur bra TinyML kan är lösa typiska ML-uppgifter. READ MORE

  6. 5. Thermal human detection for Search & Rescue UAVs

    University essay from KTH/Maskinkonstruktion (Inst.)

    Author : Tobias Wiklund-Oinonen; [2022]
    Keywords : Mechatronics; drone; object detection; search rescue; thermal camera; UAV; SAR; YOLO; EfficientDet; TensorFlow; Mekatronik; drönare; värmekamera; räddningsuppdrag; UAV; SAR; YOLO; EfficientDet; TensorFlow;

    Abstract : Unmanned Aerial Vehicles (UAVs) could play an important role in Search & Rescue (SAR) operations thanks to their ability to cover large, remote, or inaccessible search areas quickly without putting any personnel at risk. As UAVs are becoming autonomous, the problem of identifying humans in a variety of conditions can be solved with computer vision implemented with a thermal camera. READ MORE