Results 241 to 250 of about 7,238,657 (296)

Spatial and Volumetric Characteristics of Glioblastoma: Associations With Clinical Presentation and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou, Marc Jaskir, Julian Gal, Yombe Fonkeu, Christos Davatzikos, MacLean P. Nasrallah, Jose Garcia, Rubo Xing, Stephen J. Bagley, Arati Desai, Richard E. Phillips, Steven Tobochnik, Colin A. Ellis, James J. Gugger, Nishant Sinha, Joel M. Stein, Kathryn A. Davis   +16 more
wiley   +1 more source

Task-adaptive multimodal molecular representations for structure-sensitive property prediction. [PDF]

Chem Sci
Lin S, Zhai S, Wang S, Zhan X, Li Y, Li W, Qin L, Shi L, Tian Y, Xu K, Zhou K, Gu C, Liu H, Yao X.   +13 more
europepmc   +1 more source

Stretcher: a learning-based framework for deformation-robust keypoint descriptors. [PDF]

Int J Comput Assist Radiol Surg
von Witzleben C, Haouchine N.
europepmc   +1 more source

Human-Constrained AI-Assisted Identification of Defect-Topology Relations for Mechanical Degradation in Porous Solids: A Discrete-Element Study. [PDF]

Materials (Basel)
Zhang Y, Liu Y, Xie H.
europepmc   +1 more source

Joint spectro-temporal and perceptual feature learning using a dual-track attention network for music genre classification. [PDF]

Front Artif Intell
Hari VA, Jenish SA, Karthik R, Ananya M.
europepmc   +1 more source

When high accuracy misleads in literature-derived machine learning for deep eutectic solvent recommendation. [PDF]

RSC Adv
Faraji H, Mendez-Perez JA, Rodríguez-Ramos R, Socas-Rodríguez B, Herrera Herrera AV.   +4 more
europepmc   +1 more source

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Local feature descriptor using entropy rate

Neurocomputing, 2016
Over the past decades, an increasing number of local feature descriptors have been proposed in the community of computer vision and pattern recognition. Although they have achieved impressive results in many applications, how to find a balance between accuracy and computational efficiency is still an open issue.
Pu Yan, Dong Liang 0009, Jun Tang 0007, Ming Zhu   +3 more
exaly   +3 more sources

A local multiple patterns feature descriptor for face recognition

Neurocomputing, 2020
Abstract Human perception of a signal depends on the ratio of the change of stimulus to the stimulus itself while the change of stimulus to the stimulus itself is usually ignored in hand-crafted feature descriptors. However, it is important for extracting discriminant feature. To address this problem, we firstly develop a local multiple patterns (LMP)
Wankou Yang
exaly   +3 more sources

Fast image segmentation for local feature descriptors

2017 25th Signal Processing and Communications Applications Conference (SIU), 2017
Local feature descriptors are the most frequently used feature representation in many Computer Vision problems. In particular, high level semantic information extraction from low-level features in classification and retrieval is also quite successful. Region based approaches to classification and retrieval have become very popular.
BİLGE, HASAN ŞAKİR, Celik, Ceyhun
openaire   +3 more sources