Results 51 to 60 of about 38,175 (260)

A Homotopy Iterative Hard Thresholding Algorithm With Extreme Learning Machine for Scene Recognition

IEEE Access, 2018
Vision-based scene recognition aims to find a semantic explanation of a scene image. First, how to learn a sparse feature representation by mapping each cluster of patches into few dimensions is one challenging issue.
Yuanlong Yu, Zhenzhen Sun, Wenxing Zhu, Jason Gu   +3 more
doaj   +1 more source

Recursive Sparse, Spatiotemporal Coding [PDF]

2009 11th IEEE International Symposium on Multimedia, 2009
We present a new approach to learning sparse, spatiotemporal codes in which the number of basis vectors, their orientations, velocities and the size of their receptive fields change over the duration of unsupervised training. The algorithm starts with a relatively small, initial basis with minimal temporal extent. This initial basis is obtained through
Thomas L. Dean, Richard Washington, Greg Corrado   +2 more
openaire   +1 more source

Electroencephalographic Normalization as a Biomarker of Clinical Recovery in Down Syndrome Regression Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Down syndrome regression disorder is a syndrome characterized by subacute loss of cognitive, behavioral, and functional abilities in individuals with Down syndrome. Electroencephalography abnormalities are frequently observed during evaluation, but it remains unclear whether these findings represent a dynamic marker of disease ...
Jonathan D. Santoro, Mackenzie Silverman, Maeve C. Lucas, Mariam M. Yousuf, Samuel T. Otey, Stella V. Gray, Brittany Jordan, Madeline D. Kahan, Latanya D. Agurs, Michelle Van Hirtum Das, Deborah Holder, Devin King, Eileen A. Quinn, Ryan Kammeyer, Michael S. Rafii   +14 more
wiley   +1 more source

An Efficient Compressive Sensing Event-Detection Scheme for Internet of Things System Based on Sparse-Graph Codes

Sensors, 2023
This work studied the event-detection problem in an Internet of Things (IoT) system, where a group of sensor nodes are placed in the region of interest to capture sparse active event sources. Using compressive sensing (CS), the event-detection problem is
Jun Cai, Xin Xu, Hongpeng Zhu, Jian Cheng   +3 more
doaj   +1 more source

Learned Convolutional Sparse Coding [PDF]

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
We propose a convolutional recurrent sparse auto-encoder model. The model consists of a sparse encoder, which is a convolutional extension of the learned ISTA (LISTA) method, and a linear convolutional decoder. Our strategy offers a simple method for learning a task-driven sparse convolutional dictionary (CD), and producing an approximate convolutional
Sreter, Hillel, Giryes, Raja
openaire   +2 more sources

Evaluation of a Novel Electric Health Record Sidecar Application to Display Rheumatoid Arthritis Clinical Outcomes During Clinic Visits: Results of a Stepped‐Wedge Cluster Randomized Pragmatic Trial

Arthritis Care &Research, EarlyView.
Objective We developed a novel electronic health record sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk, Jing Li, Cathy Nasrallah, Cherish Wilson, Alicia Hamblin, Christine Hariz, Cammie Young, Stephen Shiboski, Emma Kersey, Mary Nakamura, Judith F. Ashouri, Mehrdad Matloubian, Andrew J. Gross, Jennifer Barton, Beth Berrean, Jonathan Prugh, Jinoos Yazdany   +16 more
wiley   +1 more source

Improving MRAM Performance with Sparse Modulation and Hamming Error Correction

Sensors
With the rise of the Internet of Things (IoT), smart sensors are increasingly being deployed as compact edge processing units, necessitating continuously writable memory with low power consumption and fast access times.
Nam Le, Thien An Nguyen, Jong-Ho Lee, Jaejin Lee   +3 more
doaj   +1 more source

Multiple instance learning tracking method with local sparse representation

IET Computer Vision, 2013
When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them.
Chengjun Xie, Jieqing Tan, Peng Chen, Jie Zhang, Lei He   +4 more
doaj   +1 more source

Discriminative sparse neighbor coding [PDF]

Multimedia Tools and Applications, 2015
Sparse coding has received extensive attention in the literature of image classification. Traditional sparse coding strategies tend to approximate local features in terms of a linear combination of basis vectors, without considering feature neighboring relationships.
Xiao Bai 0001, Cheng Yan, Peng Ren 0001, Lu Bai 0001, Jun Zhou 0001   +4 more
openaire   +2 more sources

Risk of Retinopathy Associated with Long‐Term Use of Hydroxychloroquine in Patients with Rheumatic Diseases: A Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective We aimed to estimate the prevalence and cumulative incidence of hydroxychloroquine retinopathy (HCQ‐R) and its risk factors among patients receiving long‐term HCQ with rheumatic diseases through a systematic review and meta‐analysis of observational studies that used spectral‐domain optical coherence tomography (SD‐OCT) for screening ...
Narsis Daftarian, Chloe Yue, Steve D Levasseur, Hui Xie, J. Antonio Avina‐Zubieta   +4 more
wiley   +1 more source