Sökning: "Video prediction"

Visar resultat 1 - 5 av 89 uppsatser innehållade orden Video prediction.

1. 1. Prediction Models for TV Case Resolution Times with Machine Learning

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

   Författare :Borja Javierre I Moyano; [2023]
   Nyckelord :Datasets; Machine Learning ML ; Prediction; Resolution Time RT ; Solve Time; TV Cases; Trouble Tickets TT ; Customer-Related Trouble Tickets Resolution Time; CRM system; BI system; Telecommunications; Dataset; Machine Learning ML ; Prediction; Resolution Time; Solve Time; TV Cases; Trouble Tickets TT ; Kundrelaterade problem Tickets Resolution tid; CRM-system; BI-system; Telekommunikationer.;

   Sammanfattning : TV distribution and stream content delivery of video over the Internet, since is made up of complex networks including Content Delivery Networks (CDNs), cables and end-point user devices, that is very prone to issues appearing in different levels of the network ending up affecting the final customer’s TV services. When a problem affects the customer, and this prevents from having a proper TV delivery service in devices used for stream purposes, the issue is reported through a call, a TV case is opened and the company’s customer handling agents start supervising it to solve the problem as soon as possible. LÄS MER

3. 2. Regularizing Vision-Transformers Using Gumbel-Softmax Distributions on Echocardiography Data

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

   Författare :Alfred Nilsson; [2023]
   Nyckelord :Deep Learning; Vision-Transformers; Echocardiography; Feature Selection; Gumbel-Softmax; Concrete Autoencoders; Regression; Djupinlärning; Vision-Transformers; Ekokardiografi; Feature Selection; GumbelSoftmax; Concrete Autoencoders; Regression;

   Sammanfattning : This thesis introduces an novel approach to model regularization in Vision Transformers (ViTs), a category of deep learning models. It employs stochastic embedded feature selection within the context of echocardiography video analysis, specifically focusing on the EchoNet-Dynamic dataset. LÄS MER

4. 3. Image-Guided Zero-Shot Object Detection in Video Games : Using Images as Prompts for Detection of Unseen 2D Icons

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

   Författare :Axel Larsson; [2023]
   Nyckelord :Computer Vision; Deep learning; Machine learning; Object detection; Zeroshot; Datorseende; Djupinlärning; Maskininlärning; Objektdetektering; Zero-shot;

   Sammanfattning : Object detection deals with localization and classification of objects in images, where the task is to propose bounding boxes and predict their respective classes. Challenges in object detection include large-scale annotated datasets and re-training of models for specific tasks. LÄS MER

5. 4. Fog detection using an artificial neural network

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Quanwei Li; Tiancheng Ma; [2023]
   Nyckelord :Machine Learning; Deep Learning; Image Analysis; Computer Vision; Mathematics and Statistics;

   Sammanfattning : This project studies a method of image-based fog detection directly from a camera without using the transmissometer. Fog can be detected using transmissometers which could be a very costly approach. This thesis presents an image-based approach for fog detection using Artificial Neural networks. LÄS MER

7. 5. Computer-vision as an ErrorRecognition Tool for IndustryProduction Lines : A comparative study of models and neural networks

   Uppsats för yrkesexamina på avancerad nivå, Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)

   Författare :André Lundholm; [2023]
   Nyckelord :Computer-vision; Machine Learning; Wood Industry; Neural Network; Convolutional Neural Network; Anomaly Detection; Outlier Detection; Object Detection;

   Sammanfattning : To use machine learning as a tool to help humans perform tasks is a common occurrence these days. Machine learning integration in the wood processing industry however, is more rare. Therefore it is suitable to research if machine learning works for some problem in this area. LÄS MER