Essays about: "Fully Convolutional Neural Networks"

Showing result 6 - 10 of 74 essays containing the words Fully Convolutional Neural Networks.

  1. 6. Neural Network-Based Residential Water End-Use Disaggregation

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

    Author : Cajsa Pierrou; [2023]
    Keywords : Residential water end-use; Flow disaggregation; Time series classification; Artificial neural network; Smart water meter; Slutanvändning av vatten i hushåll; Flödesdisaggregering; Tidsserieklassificering; Artificiella neurala nätverk; Smart vattenmätare;

    Abstract : Sustainable management of finite resources is vital for ensuring livable conditions for both current and future generations. Measuring the total water consumption of residential households at high temporal resolutions and automatically disaggregating the sole signal into classified end usages (e.g. READ MORE

  3. 7. Meta-Pseudo Labelled Multi-View 3D Shape Recognition

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

    Author : Fehmi Ayberk Uçkun; [2023]
    Keywords : 3D shape recognition; 3D object classification; 3D shape retrieval; 3D object retrieval; Automatic labelling; Semi-supervised learning; Pseudo labelling; Meta Pseudo Labelling; Multi-View Convolutional Neural Networks; Shape descriptors; Multi-view representations; Deeplearning; 3D-formigenkänning; 3D-objektklassificering; 3D-formhämtning; Hämtning av 3D-objekt; Automatisk märkning; Halv-vägledd lärning; Pseudomärkning; Meta Pseudo-märkning; Multi-View Faltningsnät; Formbeskrivningar; Multi-view representation; Djupinlärning;

    Abstract : The field of computer vision has long pursued the challenge of understanding the three-dimensional world. This endeavour is further fuelled by the increasing demand for technologies that rely on accurate perception of the 3D environment such as autonomous driving and augmented reality. READ MORE

  4. 8. A Comparison of CNN and Transformer in Continual Learning

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

    Author : Jingwen Fu; [2023]
    Keywords : Convolutional Neural Network; Transformer; Continual Learning; Image Classification; Faltade Neurala Nätverk; Transformator; Kontinuerligt Lärande; Bildklassificering;

    Abstract : Within the realm of computer vision tasks, Convolutional Neural Networks (CNN) and Transformers represent two predominant methodologies, often subject to extensive comparative analyses elucidating their respective merits and demerits. This thesis embarks on an exploration of these two models within the framework of continual learning, with a specific focus on their propensities for resisting catastrophic forgetting. READ MORE

  5. 9. Low-power Acceleration of Convolutional Neural Networks using Near Memory Computing on a RISC-V SoC

    University essay from Lunds universitet/Institutionen för elektro- och informationsteknik

    Author : Kristoffer Westring; Linus Svensson; [2023]
    Keywords : FPGA; ASIC; Near Memory Computing; RISC-V; Convolutional Neural Network; Technology and Engineering;

    Abstract : The recent peak in interest for artificial intelligence, partly fueled by language models such as ChatGPT, is pushing the demand for machine learning and data processing in everyday applications, such as self-driving cars, where low latency is crucial and typically achieved through edge computing. The vast amount of data processing required intensifies the existing performance bottleneck of the data movement. READ MORE

  6. 10. Machine Learning-based MIMO Indoor Positioning

    University essay from Lunds universitet/Institutionen för elektro- och informationsteknik

    Author : Qiyi Chen; [2023]
    Keywords : Technology and Engineering;

    Abstract : The most widely used positioning system is Global Navigation Satellite System (GNSS), which uses traditional positioning techniques and cannot achieve satisfactory positioning performance in indoor scenarios due to Non-Line-of-Sight (NLoS) transmission. Fingerprinting is a non-traditional positioning technique that is robust to NLoS transmission in indoor scenarios. READ MORE