Results 101 to 110 of about 387,320 (324)
AlgorithmsThis paper proposes a novel hybrid approach that combines unsupervised feature extraction through clustering and unsupervised feature selection for data reduction, specifically targeting high-dimensional data.
David Gutman +3 more
doaj +1 more source
Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics
Advanced Robotics Research, EarlyView.This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang +5 more
wiley +1 more source
CGUFS: A clustering-guided unsupervised feature selection algorithm for gene expression data. [PDF]
J King Saud Univ Comput Inf Sci, 2023 Xu Z +6 more
europepmc +1 more source
The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
Advanced Robotics Research, EarlyView.Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley +1 more source
Feature Selection for Linear SVM with Provable Guarantees
, 2015 We give two provably accurate feature-selection techniques for the linear SVM. The algorithms run in deterministic and randomized time respectively. Our algorithms can be used in an unsupervised or supervised setting.
Drineas, Petros +2 more
core
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling
Advanced Robotics Research, EarlyView.This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou +4 more
wiley +1 more source
Unsupervised feature selection based on incremental forward iterative Laplacian score. [PDF]
Artif Intell Rev, 2023 Jiang J, Zhang X, Yang J.
europepmc +1 more source
Unsupervised Feature Selection Using Feature Density Functions
, 2009 {"references": ["U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, \"From data mining to\nknowledge discovery in databases\", AI Magazine, vol. 17, 1996, pp. 37-\n54.", "M. Lindenbaum, S. Markovitch, D. Rusakov, \"Selective sampling for\nnearest neighbor classifiers\", Machine learning, vol. 54, 2004, pp. 125-\n152.", "A.I. Schein, L.H.
Alibeigi, Mina +2 more
openaire +1 more source
From Lab to Landscape: Environmental Biohybrid Robotics for Ecological Futures
Advanced Robotics Research, EarlyView.This Perspective explores environmental biohybrid robotics, integrating living tissues, microorganisms, and insects for operation in real‐world ecosystems. It traces the leap from laboratory experiments to forests, wetlands, and urban environments and discusses key challenges, development pathways, and opportunities for ecological monitoring and ...
Miriam Filippi
wiley +1 more source