Sökning: "image annotation"
Visar resultat 1 - 5 av 49 uppsatser innehållade orden image annotation.
1. Automatic Semantic Segmentation of Indoor Datasets
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. LÄS MER
2. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment
Master-uppsats,Sammanfattning : 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. LÄS MER
3. Image Quality Assessment Pipeline and Semi-Automated Annotation method for Synthetic Data
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Predicting human emotions through facial expression, particularly in relation to medication field such as clinical trial settings, has garnered scientific interest in recent years due to significant understanding of the impact of treatment on emotions and social functioning. This thesis aims to improve performance of a FER model using large scale of synthetic data. LÄS MER
4. Self-learning for 3D segmentation of medical images from single and few-slice annotation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Training deep-learning networks to segment a particular region of interest (ROI) in 3D medical acquisitions (also called volumes) usually requires annotating a lot of data upstream because of the predominant fully supervised nature of the existing stateof-the-art models. To alleviate this annotation burden for medical experts and the associated cost, leveraging self-learning models, whose strength lies in their ability to be trained with unlabeled data, is a natural and straightforward approach. LÄS MER
5. Automated annotation scheme for extending bounding box representation to detect ship locations.
Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Bounding boxes often provide limited information about the shape and location of an object on an image. Their limitations lie in their reduced ability to correctly represent objects that have complex shapes or are located at an angle. LÄS MER