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Full-Text Articles in Physical Sciences and Mathematics
Wildfire Spread Prediction Using Attention Mechanisms In U-Net, Kamen Haresh Shah, Kamen Haresh Shah
Wildfire Spread Prediction Using Attention Mechanisms In U-Net, Kamen Haresh Shah, Kamen Haresh Shah
Master's Theses
An investigation into using attention mechanisms for better feature extraction in wildfire spread prediction models. This research examines the U-net architecture to achieve image segmentation, a process that partitions images by classifying pixels into one of two classes. The deep learning models explored in this research integrate modern deep learning architectures, and techniques used to optimize them. The models are trained on 12 distinct observational variables derived from the Google Earth Engine catalog. Evaluation is conducted with accuracy, Dice coefficient score, ROC-AUC, and F1-score. This research concludes that when augmenting U-net with attention mechanisms, the attention component improves feature suppression …
Soarnet, Deep Learning Thermal Detection For Free Flight, Jake T. Tallman
Soarnet, Deep Learning Thermal Detection For Free Flight, Jake T. Tallman
Master's Theses
Thermals are regions of rising hot air formed on the ground through the warming of the surface by the sun. Thermals are commonly used by birds and glider pilots to extend flight duration, increase cross-country distance, and conserve energy. This kind of powerless flight using natural sources of lift is called soaring. Once a thermal is encountered, the pilot flies in circles to keep within the thermal, so gaining altitude before flying off to the next thermal and towards the destination. A single thermal can net a pilot thousands of feet of elevation gain, however estimating thermal locations is not …
Bayesian Methods And Machine Learning For Processing Text And Image Data, Yingying Gu
Bayesian Methods And Machine Learning For Processing Text And Image Data, Yingying Gu
Theses and Dissertations
Classification/clustering is an important class of unstructured data processing problems. The classification (supervised, semi-supervised and unsupervised) aims to discover the clusters and group the similar data into categories for information organization and knowledge discovery. My work focuses on using the Bayesian methods and machine learning techniques to classify the free-text and image data, and address how to overcome the limitations of the traditional methods. The Bayesian approach provides a way to allow using more variations(numerical or categorical), and estimate the probabilities instead of explicit rules, which will benefit in the ambiguous cases. The MAP(maximum a posterior) estimation is used to …
Propagated Image Segmentation Using Edge-Weighted Centroidal Voronoi Tessellation Based Methods, Youjie Zhou
Propagated Image Segmentation Using Edge-Weighted Centroidal Voronoi Tessellation Based Methods, Youjie Zhou
Theses and Dissertations
Propagated image segmentation is the problem of utilizing the existing segmentation of an image for obtaining a new segmentation of, either a neighboring image in a sequence, or the same image but in different scales. We name these two cases as the inter-image propagation and the intra-image propagation respectively. The inter-image propagation is particularly important to material science, where efficient and accurate segmentation of a sequence of 2D serial-sectioned images of 3D material samples is an essential step to understand the underlying micro-structure and related physical properties. For natural images with objects in different scales, the intra-image propagation, where segmentations …
Automated Classification Of Malignant Melanoma Based On Detection Of Atypical Pigment Network In Dermoscopy Images Of Skin Lesions, Nabin K. Mishra
Automated Classification Of Malignant Melanoma Based On Detection Of Atypical Pigment Network In Dermoscopy Images Of Skin Lesions, Nabin K. Mishra
Doctoral Dissertations
“Melanoma causes more deaths than any other form of skin cancer. Early melanoma detection is important to prevent progression to a more deadly stage. Automated computer-based identification of melanoma from dermoscopic images of skin lesions is the most efficient method in early diagnosis. An automated melanoma identification system must include multiple steps, involving lesion segmentation, feature extraction, feature combination and classification. In this research, a classifier-based approach for automatically selecting a lesion border mask for segmentation of dermoscopic skin lesion images is presented. A logistic regression based model selects a single lesion border mask from multiple border masks generated by …