Essays about: "Tidsföljder"

Found 3 essays containing the word Tidsföljder.

  1. 1. Simulation and time-series analysis for Autonomous Emergency Braking systems

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

    Author : Zhiying Xu; [2021]
    Keywords : Autonomous Driving AD ; CARLA; Autonomous Emergency Braking AEB ; Deep Learning; Time-series analysis; Autonom körning; CARLA; Autonomt nödsystem; Djup lärning; Tidsföljder;

    Abstract : One central challenge for Autonomous Driving (AD) systems is ensuring functional safety. This is affected by all parts of vehicle automation systems: environment perception, decision making, and actuation. READ MORE

  3. 2. Causal discovery in conditional stationary time-series data : Towards causal discovery in videos

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

    Author : Carles Balsells Rodas; [2021]
    Keywords : Causality; Causal discovery; Neural networks; Graph neural network; Time series; Non-stationary; Orsakssamband; Kausal upptäckt; Neurala nätverk; Diagram Neurala nätverk; Tidsföljder; Icke-stationär;

    Abstract : Performing causal reasoning in a scene is an inherent mechanism in human cognition; however, the majority of approaches in the causality literature aiming for this task still consider constrained scenarios, such as simple physical systems or stationary time-series data. In this work we aim for causal discovery in videos concerning realistic scenarios. READ MORE

  4. 3. Experimental Study on Machine Learning with Approximation to Data Streams

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

    Author : Jiani Jiang; [2019]
    Keywords : Data Streaming; Time Series; Data Compression; Machine Learning; Efficient Data Transportation; Dataströmning; Tidsföljder; Datakomprimering; Maskininlärning; Effektiv datatranspor;

    Abstract : Realtime transferring of data streams enables many data analytics and machine learning applications in the areas of e.g. massive IoT and industrial automation. Big data volume of those streams is a significant burden or overhead not only to the transportation network, but also to the corresponding application servers. READ MORE