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Browsing by Subject "Deep Learning"
Now showing items 1-18 of 18
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Automatic Concrete Defect Identification by Silencing Features of Deep Neural Network
(2020)An autonomous concrete crack inspection system is necessary for preventing hazardous incidents arising from deteriorated concrete surfaces. In this thesis, we represent a concrete crack detection framework to aid the process ... -
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Automatic Extraction of Joint Characteristics from Rock Mass Surface Point Cloud Using Deep Learning
(2021)A methodology for a computerized recognition of joint sets on 3D point cloud models of rock masses using deep learning is presented. The process starts with classifying joints on a 3D rock mass surface through training a ... -
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Computational Methods for Delineating Multiple Nuclear Phenotypes from Different Imaging Modalities
(2019)Characterizing histopathology or organoid models of breast cancer can provide fundamental knowledge that will lead to a better understanding of tumors, response to therapeutic agents, and discovery of new targeted therapies. ... -
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Deep Learning Based Concrete Distress Detection System for Civil Infrastructure
(2022)In most civil concrete structures, the inspection of structural health is essential. A periodical inspection process ensures that the infrastructure will meet the functional requirements properly or not. To avoid hazardous ... -
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Deep Learning Based Robust Human Body Segmentation for Pose Estimation from RGB-D Sensors
(2016)This project focuses on creating a system for human body segmentation meant to be used for pose estimation. Recognizing a human figure in a cluttered environment is a challenging problem. Current systems for pose estimation ... -
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Deep Learning-Based Exploration Path Planning
(2020)In this thesis, two deep learning-based path planning methods for autonomous exploration of subterranean environments using aerial robots are presented. One approach utilizes imitation learning, where training samples are ... -
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Deep Learning-Based Part Labeling of Tree Components in Point Cloud Data
(2022)Point cloud data analysis plays a crucial role in forest management, remote sensing, and wildfire monitoring and mitigation, necessitating robust computer algorithms and pipelines for segmentation and labeling of tree ... -
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Deep Learning-Based Part Labeling of Tree Components in Point Cloud Data
(2023)Point cloud data analysis plays a crucial role in forest management, remote sensing, and wildfire monitoring and mitigation, necessitating robust computer algorithms and pipelines for segmentation and labeling of tree ... -
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Deep Representation Learning with Limited Data for Biomedical Image Synthesis, Segmentation, and Detection
(2023)Biomedical imaging requires accurate expert annotation and interpretation that can aid medical staff and clinicians in automating differential diagnosis and solving underlying health conditions. With the advent of Deep ... -
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Detecting and Mitigating Adversarial Attack
(2022)Automating arrhythmia detection from ECG requires a robust and trusted system that retains high accuracy under electrical disturbances. Deep neural networks have become a popular technique for tracing ECG signals, outperforming ... -
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Generative Adversarial Networks for Synthesizing Medical Images of Multiple Modalities
(2020)Deep learning architectures have revolutionized the field of medical image analysis and consistently achieve state-of-the-art accuracy by learning from high volumes of data. Despite these advances, differential diagnoses ... -
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Global Ensemble Streamflow and Flood Modeling with Application of Large Data Analytics, Deep learning and GIS
(2019)ABSTRACTFlooding is one of the most dangerous natural disasters that repeatedly occur globally, and flooding frequently leads to major urban, financial, anthropogenic, and environmental impacts in the subjected area. ... -
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Grid Power Quality with FACTS Devices and Renewable Energy Sources Using Deep Learning Algorithms
(2019)Modern customers use many sensitive devices comprised of power electronics that are quite sensitive to power quality (PQ) disturbances in the supply network. From worldwide customer surveys, complaints on PQ related ... -
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Investigating Ensembles of Single-class Classifiers for Multi-class Classification
(2023)Traditional methods of multi-class classification in machine learning involve the use of a monolithic feature extractor and classifier head trained on data from all of the classes at once. These architectures (especially ... -
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PATIENT CLASSIFICATION USING DEEP LEARNING
(2019)With diseases like Alzheimer's and Influenza still claiming lives, there have been a lot of methods developed in order to combat these diseases. There is a possibility that the key to finding susceptibility towards a disease ... -
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Rewind: A Music Transcription Method
(2016)Music is commonly recorded, played, and shared through digital audio formatssuch as wav, mp3, and various others. These formats are easy to use, but they lackthe symbolic information that musicians, bands, and other artists ... -
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Towards Resilient Models: A Deep Learning Odyssey through Mammographic Images
(2023)Recent advancements in deep learning have revolutionized the landscape of breast cancer diagnosis and analysis. While these strides have been remarkable, challenges persist in developing robust and accurate models tailored ... -
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Towards Scalable, Private and Practical Deep Learning
(2022)Deep Learning (DL) models have drastically improved the performance of Artificial Intelligence (AI) tasks such as image recognition, word prediction, translation, among many others, on which traditional Machine Learning ...