Essays about: "Network performance enhancing techniques"

Showing result 1 - 5 of 11 essays containing the words Network performance enhancing techniques.

  1. 1. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders

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

    Author : Kobe Moerman; [2023]
    Keywords : 3D pose estimation; Joint landmarks; Variational autoencoder; Multi-task model; Loss discrimination; Latent-space modulation; Depth map; 3D-positionsuppskattning; Gemensamma landmärken; Variationell autoencoder; Multitask-modell; Förlustdiskriminering; Latent-space-modulering; Djupkarta;

    Abstract : Human pose estimation (HPE) constitutes a fundamental problem within the domain of computer vision, finding applications in diverse fields like motion analysis and human-computer interaction. This paper introduces innovative methodologies aimed at enhancing the accuracy and robustness of 3D joint estimation. READ MORE

  3. 2. Evaluation and Optimization of LTE-V2X Mode 4 under Aperiodic Messages of Variable Size

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

    Author : Md Mamunur Rashid; [2023]
    Keywords : LTE-V2X; aperiodic; variable size; CAM; Technology and Engineering;

    Abstract : Vehicular networks connect vehicles for improved road safety and efficiency with the assistance of wireless information exchange. Vehicular networks are based on the frequent broadcast of awareness messages referred to as CAM (Cooperative Awareness Messages) or BSM (Basic Safety Message) in the ETSI and SAE standards, respectively. READ MORE

  4. 3. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods

    University essay from KTH/Fysik

    Author : Jeanette Marie Victoria Skeppland Hole; [2023]
    Keywords : ECG; ECG-analysis; QRS detector; Artificial Intelligence; Machine Learning; Deep neural networks; Long short-term memory; Convolutional neural network; Multilayer perceptron; EKG; EKG-analys; QRS detektor; Artificiell intelligens; Maskininlärning; Djupa neurala nätverk; Long short-term memory; Convolutional neural network; Multilayer perceptron;

    Abstract : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). READ MORE

  5. 4. Finding Causal Relationships Among Metrics In A Cloud-Native Environment

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

    Author : Suresh Rishi Nandan; [2023]
    Keywords : Causality; Causal Discovery; Bayesian Network; Conditional Independence; Partial Correlation; Ensemble Causal Discovery; Anomaly Detection; Causal Graphs; Causality; Causal Discovery; Bayesian Network; Conditional Indeberoende; partiell korrelation; Ensemble Causal Discovery; Anomali Detektion; kausala grafer;

    Abstract : Automatic Root Cause Analysis (RCA) systems aim to streamline the process of identifying the underlying cause of software failures in complex cloud-native environments. These systems employ graph-like structures to represent causal relationships between different components of a software application. READ MORE

  6. 5. Developing a highly accurate, locally interpretable neural network for medical image analysis

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

    Author : Rony David Ventura Caballero; [2023]
    Keywords : XAI; Interpretability; Computer vision; Pediatric pneumonia; Chest radiograph;

    Abstract : Background Machine learning techniques, such as convolutional networks, have shown promise in medical image analysis, including the detection of pediatric pneumonia. However, the interpretability of these models is often lacking, compromising their trustworthiness and acceptance in medical applications. READ MORE