Essays about: "computer networks design"

Showing result 1 - 5 of 80 essays containing the words computer networks design.

  1. 1. Deep Learning Model Deployment for Spaceborne Reconfigurable Hardware : A flexible acceleration approach

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

    Author : Javier Ferre Martin; [2023]
    Keywords : Space Situational Awareness; Deep Learning; Convolutional Neural Networks; FieldProgrammable Gate Arrays; System-On-Chip; Computer Vision; Dynamic Partial Reconfiguration; High-Level Synthesis; Rymdsituationstänksamhet; Djupinlärning; Konvolutionsnätverk; Omkonfigurerbara Field-Programmable Gate Arrays FPGAs ; System-On-Chip SoC ; Datorseende; Dynamisk partiell omkonfigurering; Högnivåsyntes.;

    Abstract : Space debris and space situational awareness (SSA) have become growing concerns for national security and the sustainability of space operations, where timely detection and tracking of space objects is critical in preventing collision events. Traditional computer-vision algorithms have been used extensively to solve detection and tracking problems in flight, but recently deep learning approaches have seen widespread adoption in non-space related applications for their high accuracy. READ MORE

  3. 2. Emulation of Network Device Behaviour for Robot Controller Testing

    University essay from Mälardalens universitet/Akademin för innovation, design och teknik

    Author : Muhamed Opacin; [2023]
    Keywords : emulation; software testing; robotics; industrial robots; computer networks; network protocols; i o devices; network traffic; network traffic replay;

    Abstract : The testing of software for robot controllers has become increasingly difficult as robotic systems become more complex. As the complexity of the systems increases, the number of hardware systems that the robot relies on also grows. READ MORE

  4. 3. Spatiotemporal Selves on a Location-Based Social Network : A Postphenomenological Autoethnography of Snap Map

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

    Author : Adam Särnell; [2023]
    Keywords : postphenomenology; autoethnography; spatiotemporality; performativity; location-based social networks; postfenomenologi; autoetnografi; spatiotemporalitet; performativitet; platsbaserade sociala nätverk;

    Abstract : The location-based social network (LBSN) Snapchat allows millions of users to share their locations to others through Snap Map: a digital map that updates their position each time they open the app. While social science studies have explored sentiments, behaviors and norms among Snap Map users, there is limited research on this type of location-based social network in the field of human-computer interaction (HCI), indicating a need for expanding the understanding of the roles that this technology and its design play in shaping the experiences and interactions among users. READ MORE

  5. 4. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors

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

    Author : Cina Arjmand; [2023]
    Keywords : Artifical Intelligence; Machine Learning; Neuromorphic Engineering; Computer Vision; Technology and Engineering;

    Abstract : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. READ MORE

  6. 5. 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