Results 241 to 250 of about 26,484 (294)

Unveiling patterns: an exploration of machine learning techniques for unsupervised feature selection in single-cell data. [PDF]

Brief Bioinform
Chatterjee N, Taraskin A, Divakaran H, Jaeger N, Enriquez V, Hedrick CC, Alimadadi A.   +6 more
europepmc   +1 more source

Nonlocomotory Robotic Strategies for Dynamic Rotation Control in Terrestrial Robots: A Review

Advanced Robotics Research, EarlyView.
Terrestrial robots increasingly require rapid body rotation to maintain stability and agility in complex environments. This review shows nonlocomotory rotational control strategies that operate without ground contact, including reaction wheels, tails, bars, limbs, and thrusters.
Y. Liang, J. An, X. Zheng, D. Wang, S. Wang, X. Wang, P. Zhu, J. Pei, S. Li, J. Paripurana, Y. Han, Z. Tang, X. Gan, Q. He, X. Ma   +14 more
wiley   +1 more source

Individual-Tree DBH Estimation from Airborne LiDAR Data Using MSFS-XGBoost. [PDF]

Sensors (Basel)
Li P, Jia Y.
europepmc   +1 more source

Exploring neural manifolds across a wide range of intrinsic dimensions. [PDF]

PLoS Comput Biol
Fadanni J, Pacelli R, Zucchetta A, Rotondo P, Allegra M.   +4 more
europepmc   +1 more source

High-Content Imaging and Machine Learning Classify Phenotypical Change in Coronary Artery Endothelial Cells Caused by BPS. [PDF]

Int J Mol Sci
Ferariu LE, Movileanu G, Gaggi G, Ghinassi B, Baldassarre AD, Credico AD.   +5 more
europepmc   +1 more source

Reply to Takefuji: Limitations of Linear Dimensional Reduction Methods in Chronic Obstructive Pulmonary Disease Phenotyping. [PDF]

Am J Respir Crit Care Med
Bell AJ, Zinovyev A, Gorban AN.
europepmc   +1 more source

EEG based epileptic seizure detection using SVM fuzzy learning and metaheuristic optimization. [PDF]

Sci Rep
Badr S, Jamali J, Taghizadeh M, Adlband N, Mahdiyar O.   +4 more
europepmc   +1 more source

Supervised Nonlinear Dimensionality Reduction for Visualization and Classification

IEEE Transactions on Systems, Man, and Cybernetics, 2005
When performing visualization and classification, people often confront the problem of dimensionality reduction. Isomap is one of the most promising nonlinear dimensionality reduction techniques. However, when Isomap is applied to real-world data, it shows some limitations, such as being sensitive to noise. In this paper, an improved version of Isomap,
Xin Geng, Zhi-Hua Zhou
exaly   +4 more sources

Nonlinear dimensionality reduction with relative distance comparison

Neurocomputing, 2009
This paper proposes a new algorithm for nonlinear dimensionality reduction. Our basic idea is to explore and exploit the local geometry of the manifold with relative distance comparisons. All such comparisons derived from local neighborhoods are enumerated to constrain the manifold to be learned.
Chunxia Zhang, Shiming Xiang, Feiping Nie   +2 more
exaly   +4 more sources