Essays about: "Vision transformers."
Showing result 1 - 5 of 35 essays containing the words Vision transformers..
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1. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment
University essay fromAbstract : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. READ MORE
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2. Classifying femur fractures using federated learning
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : The rarity and subtle radiographic features of atypical femoral fractures (AFF) make it difficult to distinguish radiologically from normal femoral fractures (NFF). Compared with NFF, AFF has subtle radiological features and is associated with the long-term use of bisphosphonates for the treatment of osteoporosis. READ MORE
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3. Few-Shot Learning for Quality Inspection
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : The goal of this project is to find a suitable Few-Shot Learning (FSL) model that can be used in a fault detection system for use in an industrial setting. A dataset of Printed Circuit Board (PCB) images has been created to train different FSL models. READ MORE
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4. Learning Embeddings for Fashion Images
University essay from Linköpings universitet/DatorseendeAbstract : Today the process of sorting second-hand clothes and textiles is mostly manual. In this master’s thesis, methods for automating this process as well as improving the manual sorting process have been investigated. READ MORE
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5. Using Machine Learning to Optimize Near-Earth Object Sighting Data at the Golden Ears Observatory
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This research project focuses on improving Near-Earth Object (NEO) detection using advanced machine learning techniques, particularly Vision Transformers (ViTs). The study addresses challenges such as noise, limited data, and class imbalance. READ MORE