Sökning: "Network performance enhancing techniques"
Visar resultat 1 - 5 av 11 uppsatser innehållade orden Network performance enhancing techniques.
1. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : 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. LÄS MER
2. Evaluation and Optimization of LTE-V2X Mode 4 under Aperiodic Messages of Variable Size
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : 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. LÄS MER
3. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods
Master-uppsats, KTH/FysikSammanfattning : 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). LÄS MER
4. Finding Causal Relationships Among Metrics In A Cloud-Native Environment
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : 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. LÄS MER
5. Developing a highly accurate, locally interpretable neural network for medical image analysis
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : 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. LÄS MER