Sökning: "Data Augmentation"

Visar resultat 1 - 5 av 188 uppsatser innehållade orden Data Augmentation.

1. 1. Robust Object Recognition and Tracking with Drones

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Jiaying Wu; [2024]
   Nyckelord :;

   Sammanfattning : The Skara Skyddsängel project explores an innovative method of providing illumination for cyclists along a 20km unlit bike lane using drones. Current GNSS approach performs generally well but further improvements are need for better robustness. Consequently, this thesis project is raised to seek a robust solution in the field of computer vision. LÄS MER

3. 2. Using Synthetic Data For Object Detection on the edge in Hazardous Environments

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

   Författare :Faraz Azarnoush; Damil Sabotic; [2024]
   Nyckelord :Technology and Engineering;

   Sammanfattning : This thesis aims to evaluate which aspects are important when generating synthetic data with the purpose of running on a lightweight object detection model on an edge device. The task we constructed was to detect Canisters and whether they feature a protective valve called a Cap or not (called a No-Cap). LÄS MER

4. 3. Data Augmentation for Object Detection using Deep Reinforcement Learning

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

   Författare :Axel Andersson; Nils Hallerfelt; [2024]
   Nyckelord :Technology and Engineering;

   Sammanfattning : Data augmentation is a concept which is used to improve machine learning models for computer vision tasks. It is usually done by firstly, defining a set of functions which transforms images and secondly, applying a random selection of these functions on the images. LÄS MER

5. 4. Exploring adaptation of self-supervised representation learning to histopathology images for liver cancer detection

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Markus Jonsson; [2024]
   Nyckelord :Self-supervised learning; Representation learning; Computer vision;

   Sammanfattning : This thesis explores adapting self-supervised representation learning to visual domains beyond natural scenes, focusing on medical imaging. The research addresses the central question: "How can self-supervised representation learning be specifically adapted for detecting liver cancer in histopathology images?" The study utilizes the PAIP 2019 dataset for liver cancer segmentation and employs a self-supervised approach based on the VICReg method. LÄS MER

7. 5. Data Augmentation: Enhancing Named Entity Recognition Performance on Swedish Medical Texts

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Lucas Rosvall; Niklas Paasonen; [2023-10-05]
   Nyckelord :Machine Learning; Information Extraction; Named Entity Recognition; BERT; Data Augmentation;

   Sammanfattning : Named Entity Recognition (NER) refers to the task of locating relevant information within text sequences. Within the medical domain, it can benefit applications such as de-identifying patient records or extracting valuable data for other downstream tasks. LÄS MER