Sökning: "latency prediction"

Visar resultat 1 - 5 av 26 uppsatser innehållade orden latency prediction.

1. 1. Prediction of 5G system latency contribution for 5GC network functions

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Ziyu Cheng; [2023]
   Nyckelord :Network model; End-to-end delay; 5GC; Prediction model; CPU load; Nätverksmodell; Slutanvändare; latens; 5GC; Modell för prediktering; CPU-last;

   Sammanfattning : End-to-end delay measurement is deemed crucial for network models at all times as it acts as a pivotal metric of the model’s effectiveness, assists in delineating its performance ceiling, and stimulates further refinement and enhancement. This premise holds true for 5G Core Network (5GC) models as well. LÄS MER

3. 2. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors

   Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

   Författare :Cina Arjmand; [2023]
   Nyckelord :Artifical Intelligence; Machine Learning; Neuromorphic Engineering; Computer Vision; Technology and Engineering;

   Sammanfattning : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. LÄS MER

4. 3. Latency Prediction in 5G Networks by using Machine Learning

   Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

   Författare :Erica Elgcrona; Evrim Mete; [2023]
   Nyckelord :Technology and Engineering;

   Sammanfattning : This thesis presents a report of predicting latency in a 5G network by using deep learning techniques. The training set contained data of network parameters along with the actual latency, collected in a 5G lab environment during four different test scenarios. LÄS MER

5. 4. Using Quantization and Serialization to Improve AI Super-Resolution Inference Time on Cloud Platform

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Wai-Hong Anton Fu; [2023]
   Nyckelord :;

   Sammanfattning : AI Super-Resolution is a branch of Artificial Intelligence where the goal is to take a low-resolution image and upscale it into a high-resolution image. These models are usually deep learning models based on Convolutional Neural Networks (CNN) and/or transformers. LÄS MER

7. 5. Prediction of user actions with an Association Rules and two Neural Network models in a configuration environment

   Magister-uppsats, Linköpings universitet/Institutionen för datavetenskap

   Författare :Hampus Elinder; [2022]
   Nyckelord :;

   Sammanfattning : Extensive configurators might suffer from latency due to their complexity - something which could hurt user experience and, in turn, sales. Machine learning models could potentially learn the patterns of user actions by looking at past configuration sessions. LÄS MER