Open Advanced Search

Log in
Enterprise Plans
Sign Up

Log in
Sign Up
Enterprise Plans
Browse
Features
Pricing

DeepDyve

Advanced Search

show/hide query preview

With all of the words or DOIs:

DeepDyve's default query mode: search by keyword or DOI.

With the exact phrase:

Require these words, in this exact order. Do not surround your terms in double-quotes ("") in this field.

With at least one of the words:

Find any of these words, separated by spaces

Without the words:

Exclude each of these words, separated by spaces

With words in the article title:

Search for these terms only in the title of an article

Published between the years:

With the following authors:

Most effective as: LastName, First Name or Lastname, FN

With words in the journal name:

Search for articles published in journals where these words are in the journal name

Reset filters

Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

DeepDyve requires Javascript to function. Please enable Javascript on your browser to continue.

Advances in Data Science

Part of the Association for Women in Mathematics Series Book Series (volume 26)

Editors: Demir, Ilke; Lou, Yifei; Wang, Xu; Welker, Kathrin

DOI: 10.1007/978-3-030-79891-8

ISBN: 978-3-030-79890-1

Publisher: Springer International Publishing - Springer Journals

Jul 5, 2021

1 - 10 of 13 Chapters

LitStream

Two-stage Geometric Information Guided Image Reconstruction

Qin, Jing; Guo, Weihong

Pages: 3 –23

[In compressive sensing, it is challenging to reconstruct image of high quality from very few noisy linear projections. Existing methods mostly work well on piecewise constant images but not so well on piecewise smooth images such as natural images, medical images that contain a lot of details....
LitStream

Image Edge Sharpening via Heaviside Substitution and Structure Recovery

Deng, Liang-Jian; Guo, Weihong; Huang, Ting-Zhu

Pages: 25 –48

[In this paper, we propose a simple but efficient method to sharpen image edges. Starting from an image with blurry edges, we improve edge sharpness using transformed approximated Heaviside functions (AHFs) for better visualization. In particular, we provide an efficient method for directly...
LitStream

Two-Step Blind Deconvolution of UPC-A Barcode Images

Kim, Bohyun; Lou, Yifei

Pages: 49 –71

[Barcodes are widely used in supermarkets and tracking systems. One noticeable difficulty in barcode recognition is caused by blurring artifacts. For example, a focal blur may occur when the data is captured at a far distance, and motion blur is often inevitable under a low light condition. To...
LitStream

An Anisotropic Local Method for Boundary Detection in Images

Lund, Margaret; Howard, Marylesa; Wu, Dongsheng; Crum, Ryan S.; Miller, Dorothy J.; Akin, Minta C.

Pages: 75 –94

[Boundary detection is a powerful tool for quantitative image analysis that allows researchers to extract crucial information about a scene. Many methods rely on sharp changes in luminance, chromaticity, or texture in order to correctly predict edge locations between regions, and images without...
LitStream

Towards Learning Geometric Shape Parts

Fondevilla, Amélie; Morin, Géraldine; Leonard, Kathryn

Pages: 95 –111

[In this article, we explore the effectiveness of using neural networks to generate skeleton-based representations of shapes. Deep-learning approaches have proven very efficient to extract meaningful information from images. Our goal is to learn a mapping from a binary image of a 2D shape to a...
LitStream

Machine Learning in LiDAR 3D Point Clouds

Medina, F. Patricia; Paffenroth, Randy

Pages: 113 –133

[LiDAR point clouds contain measurements of complicated natural scenes and can be used to update digital elevation models, glacial monitoring, detecting faults and measuring uplift detecting, forest inventory, detect shoreline and beach volume changes, landslide risk analysis, habitat mapping and...
LitStream

Fitting Small Piece-Wise Linear Neural Network Models to Interpolate Data Sets

Ness, Linda

Pages: 137 –179

[The simplest neural network models for functions are compositions of layer functions, where each layer function applies a nonlinear activation function σ, which is not a polynomial, component-wise to an affine linear functions WX + B. The rows of W are referred to as ‘weights’ and B is the ‘bias...
LitStream

On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition

Ahn, Miju; Eikmeier, Nicole; Haddock, Jamie; Kassab, Lara; Kryshchenko, Alona; Leonard, Kathryn; Needell, Deanna; Madushani, R. W. M. A.; Sizikova, Elena; Wang, Chuntian

Pages: 181 –210

[There is currently an unprecedented demand for large-scale temporal data analysis due to the explosive growth of data. Dynamic topic modeling has been widely used in social and data sciences with the goal of learning latent topics that emerge, evolve, and fade over time. Previous work on dynamic...
LitStream

A Simple Recovery Framework for Signals with Time-Varying Sparse Support

Durgin, Natalie; Grotheer, Rachel; Huang, Chenxi; Li, Shuang; Ma, Anna; Needell, Deanna; Qin, Jing

Pages: 211 –230

[Sparse recovery methods have been developed to solve multiple measurement vector (MMV) problems. These methods seek to reconstruct a collection of sparse signals from a small number of linear measurements, exploiting not only the sparsity but also certain correlations between the signals....
LitStream

Role Detection and Prediction in Dynamic Political Networks

Evans, Emily; Guo, Weihong; Genctav, Asli; Tari, Sibel; Domeniconi, Carlotta; Murillo, Anarina; Chuang, Julia; AlSumait, Loulwah; Mani, Priya; El-Zehiry, Noha

Pages: 233 –252

[The interaction of users, either online or in real-life, can be modeled via a network (or graph). In such networks, users engage in activities and take on specific roles. Users who manifest similar structural and connectivity patterns assume similar roles. The analysis of a network in terms of...

results per page

Browse All eBooks

Features

Search and discover articles on DeepDyve, PubMed, and Google Scholar
Read the full-text of open access and premium content
Organize articles with folders and bookmarks
Collaborate on and share articles and folders

Info

Pricing
Enterprise Plans
Browse Journals & Topics
About DeepDyve

Help

Help
Publishers
Contact Us

Sign up for your DeepDyve account now!

Read and print from thousands of top scholarly journals.

System error. Please try again!

Continue with Facebook

By signing up, you agree to DeepDyve’s Terms of Service and Privacy Policy.

Already have an account? Log in

Save Article to Bookmarks

Bookmark this article. You can see your Bookmarks on your DeepDyve Library.

To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.

Subscribe to Journal Email Alerts

To subscribe to email alerts, please log in first, or sign up for a DeepDyve account if you don’t already have one.

Follow a Journal

To get new article updates from a journal on your personalized homepage, please log in first, or sign up for a DeepDyve account if you don’t already have one.

Our policy towards the use of cookies

All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.

cookie policy