Essays about: "neural networks applications"

Showing result 1 - 5 of 255 essays containing the words neural networks applications.

  1. 1. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks

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

    Author : Xinchen Wang; [2024]
    Keywords : Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

    Abstract : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. READ MORE

  2. 2. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

    Author : Deepthy Prasad; Swathi Hampapura Sripada; [2023]
    Keywords : multivariate - time series; anomaly detection; neural networks; autoencoders; interpretability; counterfactuals;

    Abstract : Anomaly detection plays a crucial role in various domains, such as transportation, cybersecurity, and industrial monitoring, where the timely identification of unusual patterns or outliers is of utmost importance. Traditional statistical techniques have limitations in handling complex and highdimensional data, which motivates the use of deep learning approaches. READ MORE

  3. 3. Object Recognition in Satellite imagesusing improved ConvolutionalRecurrent Neural Network

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Author : TARUN NATTALA; [2023]
    Keywords : CRNN; CNN; RNN; Machine Learning and Satellite Image Recognition.;

    Abstract : Background:The background of this research lies in detecting the images from satellites. The recognition of images from satellites has become increasingly importantdue to the vast amount of data that can be obtained from satellites. This thesisaims to develop a method for the recognition of images from satellites using machinelearning techniques. READ MORE

  4. 4. Sales forecasting for supply chain using Artificial Intelligence

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

    Author : Vaibhav Mittal; [2023]
    Keywords : AI; sales forecasting; supply chain; predictive analytics; AI; försäljningsprognoser; supply chain; predictiv analys;

    Abstract : Supply chain management and logistics are two sectors currently experiencing a transformation thanks to the advent of AI(Artificial Intelligence) technologies. Leveraging predictive analytics powered by AI presents businesses with novel opportunities to streamline their operations effectively. READ MORE

  5. 5. 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