Sökning: "noise model"
Visar resultat 1 - 5 av 781 uppsatser innehållade orden noise model.
1. Feature Selection for Microarray Data via Stochastic Approximation
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : This thesis explores the challenge of feature selection (FS) in machine learning, which involves reducing the dimensionality of data. The selection of a relevant subset of features from a larger pool has demonstrated its effectiveness in enhancing the performance of various machine learning algorithms. LÄS MER
2. Robustness Analysis of Perfusion Parameter Calculations
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cancer is one of the most common causes of death worldwide. When given optimal treatment, however, the risk of severe illness may greatly be reduced. Determining optimal treatment in turn requires evaluation of disease progression and response to potential, previous treatment. LÄS MER
3. An In-Depth study on the Utilization of Large Language Models for Test Case Generation
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : This study investigates the utilization of Large Language Models for Test Case Generation. The study uses the Large Language model and Embedding model provided by Llama, specifically Llama2 of size 7B, to generate test cases given a defined input. LÄS MER
4. Robust non-Abelian geometric phases on three-qubit spin codes
Master-uppsats, Uppsala universitet/MaterialteoriSammanfattning : Quantum holonomies are non-Abelian Geometric Phases predominantly observed in adiabatic, non-adiabatic, or measurement-based quantum evolutions. Their significance lies in their potential utility within quantum computing due to their robustness against noise throughout the parameter path. LÄS MER
5. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER