Sökning: "Utvärderingsmått"
Visar resultat 1 - 5 av 40 uppsatser innehållade ordet Utvärderingsmått.
1. Image Colorization Based on Deep Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : With the development of artificial intelligence, there is a clear trend to combine computer technology with traditional industries. In recent years, with the development of digital media technology, many methods for coloring gray-scale images have been proposed. LÄS MER
2. Regularizing Vision-Transformers Using Gumbel-Softmax Distributions on Echocardiography Data
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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
3. Representing video game style with procedurally generated content : How wave function collapse can be used to represent style in video games
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : As the video gaming industry continues to grow, developers face increasing pressure to produce innovative content swiftly and cost-effectively. Procedural Content Generation (PCG), the use of algorithms to automate content creation, offers a solution to this problem. LÄS MER
4. Evaluating Text Summarization Models on Resumes : Investigating the Quality of Generated Resume Summaries and their Suitability as Resume Introductions
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis aims to evaluate different abstractive text summarization models and techniques for summarizing resumes. It has two main objectives: investigate the models’ performance on resume summarization and assess the suitability of the generated summaries as resume introductions. LÄS MER
5. ML enhanced interpretation of failed test result
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This master thesis addresses the problem of classifying test failures in Ericsson AB’s BAIT test framework, specifically distinguishing between environment faults and product faults. The project aims to automate the initial defect classification process, reducing manual work and facilitating faster debugging. LÄS MER