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Deep Learning
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- Description:
- In recent years, we have seen the embryo of Industry 4.0 which has been promoting manufacturing processes towards the future with better efficiency, higher accuracy and better reliability. However, manufacturing precision has been restricted by the precision of metrology and material characterization. In other words, one can only manufacture parts...
- Keyword:
- Digital Image Correlation, Metrology, Industry 4.0, Photometric Stereo, and Deep Learning
- Subject:
- Mechanical engineering
- Creator:
- Yang, Ru
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 08/23/2023
- Date Created:
- 2023-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:16719 and etdadmin_upload_1012433
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- Description:
- X-ray imaging at nano and micro-scale is of great importance for the material science and defense industry. Large penetration depth and low wavelength of x-rays offer an important potential to image objects at high resolution and in a non-invasive process. While the ever-growing community is pursuing novel applications and looking...
- Keyword:
- Computed Tomography, Deep Image Priors, X-ray Ptychography, Deep Learning, Computational Imaging, and Computed Laminography
- Subject:
- Electrical engineering, Computational physics, and Computer science
- Creator:
- Barutcu, Semih
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 09/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_927076 and http://dissertations.umi.com/northwestern:16218
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- Description:
- The past decade has seen the rapid progress of deep learning, which becomes a game-changing technique in different data-intensive domains, with the availability of large scale data, cost-effective computing hardware and more advanced learning theory and algorithms. Despite of the rapid progress of deep learning methods in daily-life applications, such...
- Keyword:
- Computational Photography, Representation Learning, Dataset Construction, Data Science, Computer Vision, and Deep Learning
- Subject:
- Materials Science, Information technology, and Computer science
- Creator:
- Jiang, Weixin
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 06/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_899812 and http://dissertations.umi.com/northwestern:16024
-
- Description:
- Mammalian transcriptional regulation is well-known to be complex and highly context dependent. Different genetic and epigenetic features, including single nucleotide polymorphisms (SNPs) that function as cis- or trans-expression quantitative trait loci (eQTLs), transcription factor (TF) interaction profile with cis-regulatory elements (CREs), methylation of CpG dinucleotide sequences, and histone modification that...
- Keyword:
- Bioinformatics, Transcriptomics, Gene regulation, Deep Learning, Machine Learning, and Drug discovery
- Subject:
- Bioinformatics, Genetics, and Oncology
- Creator:
- Ji, Yanrong
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 06/28/2021
- Date Created:
- 2021-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_818497 and http://dissertations.umi.com/northwestern:15562
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- Description:
- Recently, a myriad of applications take advantage of deep learning methods to solve regression/classification problems. Although deep neural networks have shown powerful learning capability, many deep learning applications suffer from the extremely time-consuming training of the neural networks. In order to reduce the training time, researchers usually consider parallel training...
- Keyword:
- Adaptive Batch Size, Data Parallelism, Deep Learning, and Communication Cost
- Subject:
- Computer engineering
- Creator:
- Lee, Sunwoo N/A
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_772590 and http://dissertations.umi.com/northwestern:15340
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- Description:
- Deep neural networks have achieved remarkable success in the past decade on tasks that were out of reach prior to the era of deep learning. Amongst the myriad reasons for these successes are powerful computational resources, large datasets, new optimization algorithms, and modern architecture designs. Most of the reasons are...
- Keyword:
- Statistical Physics, Deep Learning, and Machine Learning
- Subject:
- Statistical physics
- Creator:
- Wei, Mingwei
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_777448 and http://dissertations.umi.com/northwestern:15367
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- Description:
- Super-resolution (SR) has become one of the most critical problems in image and video processing. In Chapter 2 of this thesis, a detailed review of existing Deep Learning (DL) techniques for addressing the SR task, with an emphasis on how DL and analytical techniques can be combined, is provided. Chapter...
- Keyword:
- Image Processing, Video Processing, Deep Learning, and Super-Resolution
- Subject:
- Electrical engineering and Computer science
- Creator:
- Lucas, Alice Marie
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 01/21/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15076 and etdadmin_upload_741221
-
- Description:
- Polymer nanocomposites are a class of advanced materials comprised of soft polymer matrix and nano-filler inclusions. While it has been found qualitatively that enhancements of material properties could be achieved by dispersing inorganic nano-particles into organic polymer matrix, the intrinsic governing principles of such composite has not been thoroughly studied...
- Keyword:
- Interphase, Data Mining, Design Optimization, Finite Element Analysis, Deep Learning, and Microstructure Characterization and Reconstruction
- Subject:
- Mechanical engineering, Computer science, and Engineering
- Creator:
- Li, Xiaolin
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/12/2020
- Date Created:
- 2018-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:14436 and etdadmin_upload_625304
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- Description:
- In this work, we explore the utility of the three main types of neural networks: feed forward, convolutional, and recurrent. While using these networks, we develop a new way to model multiagent trajectory data, explore the use of multiple activation functions for neurons at each layer of a neural network,...
- Keyword:
- Stock Prediction, Deep Learning, Basketball Trajectory, Activation Functions, and Machine Learning
- Subject:
- Engineering Sciences and Applied Mathematics
- Creator:
- Mark Harmon
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 10/14/2019
- Date Modified:
- 10/14/2019
- Date Created:
- 2018-01-01
- Resource Type:
- Dissertation