Results 81 to 90 of about 2,740,047 (370)

An Unsupervised Sentiment Classification Method Based on Multi-Level Fuzzy Computing and Multi-Criteria Fusion

IEEE Access, 2020
With the rapid growth of user-generated content, unsupervised methods that do not require label training data have gradually become a research focus in the field of sentiment classification and natural language processing.
Bingkun Wang, Weina He, Zhen Yang, Shufeng Xiong   +3 more
doaj   +1 more source

Deep Discrete Hashing with Self-supervised Pairwise Labels

, 2017
Hashing methods have been widely used for applications of large-scale image retrieval and classification. Non-deep hashing methods using handcrafted features have been significantly outperformed by deep hashing methods due to their better feature ...
A Andoni, B Fan, E Tola, H Bay, J Guo, J Song, J Song, O Russakovsky, Q Tian, R Salakhutdinov, T-T Do, Y Gong, Z Pan   +12 more
core   +1 more source

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source

Unsupervised Feature Selection Based on Ultrametricity and Sparse Training Data: A Case Study for the Classification of High-Dimensional Hyperspectral Data

Remote Sensing, 2018
In this paper, we investigate the potential of unsupervised feature selection techniques for classification tasks, where only sparse training data are available.
Patrick Erik Bradley, Sina Keller, Martin Weinmann   +2 more
doaj   +1 more source

Supervised versus unsupervised approaches to classification of accelerometry data

Ecology and Evolution, 2023
Sophisticated animal‐borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for ...
Maitreyi Sur, Jonathan C. Hall, Joseph Brandt, Molly Astell, Sharon A. Poessel, Todd E. Katzner   +5 more
doaj   +1 more source

Deep unsupervised clustering with Gaussian mixture variational autoencoders [PDF]

, 2016
We study a variant of the variational autoencoder model with a Gaussian mixture as a prior distribution, with the goal of performing unsupervised clustering through deep generative models. We observe that the standard variational approach in these models
Arulkumaran, K, Dilokthanakul, N, Garnelo, M, Lee, MCH, Mediano, PAM, Salimbeni, H, Shanahan, M   +6 more
core  

Serum Soluble Mediator Signatures of Lupus Nephritis: Histologic Features and Response to Treatment

Arthritis Care &Research, EarlyView.
Objective Lupus nephritis (LN) management remains challenging, and novel noninvasive biomarkers are needed. This study quantified serum soluble mediators in the Accelerating Medicines Partnership (AMP) LN cohort to identify biomarkers of histologic features and treatment response.
Andrea Fava, Catriona A. Wagner, Carla J. Guthridge, Susan Macwana, Wade DeJager, Melissa E. Munroe, Peter Izmirly, H. Michael Belmont, Betty Diamond, Anne Davidson, Paul J. Utz, Michael H. Weisman, Philip M. Carlucci, Maria Dall'Era, Kenneth Kalunian, Chaim Putterman, Jennifer Anolik, Jennifer L. Barnas, David Wofsy, Diane Kamen, Richard A. Furie, Deepak A. Rao, the Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus Network, Chun‐Hao Lee, Derek Fine, Manny Monroy‐Trujillo, Ummara Shah, Mariko Ishimori, Robert M. Clancy, Michael Belmont, Ming Wu, Nicole Bornkamp, Evan Der, Beatrice Goilav, Nicole Jordan, Daniel Schwartz, James Pullman, David Wofsy, Dawn Smilek, Patti Tosta, Matthias Kretzler, Celine C. Berthier, E. Steve Woodle, Dave Hildeman, Michael Brenner, Michelle Petri, Joel M. Guthridge, Jill Buyon, Judith A. James   +48 more
wiley   +1 more source

Automatic Microaneurysm Detection Using the Sparse Principal Component Analysis-Based Unsupervised Classification Method

IEEE Access, 2017
Since microaneurysms (MAs) can be seen as the earliest lesions in diabetic retinopathy, its detection plays a critical role in the diabetic retinopathy diagnosis.
W. Zhou, Chengdong Wu, Dali Chen, Yugen Yi, Wenyou Du   +4 more
semanticscholar   +1 more source

A Van der Waals Optoelectronic Synapse with Tunable Positive and Negative Post‐Synaptic Current for Highly Accurate Spiking Neural Networks

Advanced Functional Materials, EarlyView.
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon, Soeun Park, Yeong Kwon Kim, Juhwan Baek, Ki Han Kim, Seongil Yun, Hyeonchang Son, Jeongeun Choi, Byung Chul Jang, Dong‐Ho Kang   +9 more
wiley   +1 more source

Unsupervised Classification for Polarimetric Synthetic Aperture Radar Images Based on Wishart Mixture Models

Leida xuebao, 2017
Unsupervised classification is a significant step inthe automated interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, determining the number of clusters in this process is still a challenging problem. To this end, we propose
Zhong Neng, Yang Wen, Yang Xiangli, Guo Wei   +3 more
doaj   +1 more source