Sökning: "Djupt neuralt nätverk"
Visar resultat 1 - 5 av 30 uppsatser innehållade orden Djupt neuralt nätverk.
1. An efficient deep reinforcement learning approach to the energy management for a parallel hybrid electric vehicle
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : In contemporary world, the global energy crisis and raise of greenhouse gas concentration in atmosphere necessitate the energy conservation and emission reduction. Hybrid electric vehicles (HEVs) can achieve great promise in reducing fuel consumption and greenhouse gas emissions by appropriate energy management strategies (EMSs). LÄS MER
2. Automatic Detection of Structural Deformations in Batteries from Imaging data using Machine Learning : Exploring the potential of different approaches for efficient structural deformation detection
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The increasing occurrence of structural deformations in the electrodes of the jelly roll has raised quality concerns during battery manufacturing, emphasizing the need to detect them automatically with the advanced techniques. This thesis aims to explore and provide two models based on traditional computer vision (CV) and deep neural network (DNN) techniques using computed tomography (CT) scan images of jelly rolls to ensure that the product is of high quality. LÄS MER
3. Auto-Tuning Apache Spark Parameters for Processing Large Datasets
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Apache Spark is a popular open-source distributed processing framework that enables efficient processing of large amounts of data. Apache Spark has a large number of configuration parameters that are strongly related to performance. Selecting an optimal configuration for Apache Spark application deployed in a cloud environment is a complex task. LÄS MER
4. Deep Generative Modeling : An Overview of Recent Advances in Likelihood-based Models and an Application to 3D Point Cloud Generation
Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : Deep generative modeling refers to the process of constructing a model, parameterized by a deep neural network, that learns the underlying patterns and structures of the data generating process which produced the samples in a given dataset, in order to generate novel samples that resemble those in the original dataset. Deep generative models for 3D shape generation hold significant importance to various fields including robotics, medical imaging, manufacturing, computer animation and more. LÄS MER
5. Generating Extreme Value Distributions in Finance using Generative Adversarial Networks
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : This thesis aims to develop a new model for stress-testing financial portfolios using Extreme Value Theory (EVT) and General Adversarial Networks (GANs). The current practice of risk management relies on mathematical or historical models, such as Value-at-Risk and expected shortfall. LÄS MER