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Full-Text Articles in Engineering
Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan
Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan
Graduate Theses, Dissertations, and Problem Reports
The oil and gas industry has historically spent significant amount of capital to acquire large volumes of analog and digital data often left unused due to lack of digital awareness. It has instead relied on individual expertise and numerical modelling for reservoir development, characterization, and simulation, which is extremely time consuming and expensive and inevitably invites significant human bias and error into the equation. One of the major questions that has significant impact in unconventional reservoir development (e.g., completion design, production, and well spacing optimization), CO2 sequestration in geological formations (e.g., well and reservoir integrity), and engineered geothermal systems (e.g., …
Computational Mechanisms Of Face Perception, Jinge Wang
Computational Mechanisms Of Face Perception, Jinge Wang
Graduate Theses, Dissertations, and Problem Reports
The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for …
A Deep Learning Approach To Lncrna Subcellular Localization Using Inexact Q-Mer, Weijun Yi
A Deep Learning Approach To Lncrna Subcellular Localization Using Inexact Q-Mer, Weijun Yi
Graduate Theses, Dissertations, and Problem Reports
Long non coding Ribonucleic Acids (lncRNAs) can be localized to different cellular components, such as the nucleus, exosome, cytoplasm, ribosome, etc. Their biological functions can be influenced by the region of the cell they are located. Many of these lncRNAs are associated with different challenging diseases. Thus, it is crucial to study their subcellular localization. However, compared to the vast number of lncRNAs, only relatively few have annotations in terms of their subcellular localization. Conventional computational methods use q-mer profiles from lncRNA sequences and then train machine learning models, such as support vector machines and logistic regression with the profiles. …
Video And Image Super-Resolution Via Deep Learning With Attention Mechanism, Xuan Xu
Video And Image Super-Resolution Via Deep Learning With Attention Mechanism, Xuan Xu
Graduate Theses, Dissertations, and Problem Reports
Image demosaicing, image super-resolution and video super-resolution are three important tasks in color imaging pipeline. Demosaicing deals with the recovery of missing color information and generation of full-resolution color images from so-called Color filter Array (CFA) such as Bayer pattern. Image super-resolution aims at increasing the spatial resolution and enhance important structures (e.g., edges and textures) in super-resolved images. Both spatial and temporal dependency are important to the task of video super-resolution, which has received increasingly more attention in recent years. Traditional solutions to these three low-level vision tasks lack generalization capability especially for real-world data. Recently, deep learning methods …