Results 81 to 90 of about 136,861 (303)
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
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
Statistical Models for Unsupervised Learning of Morphology and POS Tagging [PDF]
, 2011 This thesis concentrates on two fields in natural language processing. The main contribution of the thesis is in the field of morphology learning. Morphology is the study of how words are formed combining different language constituents (called morphemes)
Can, Burcu
core
Adversarial Robustness on Image Classification With
IEEE AccessAttacks and defences in adversarial machine learning literature have primarily focused on supervised learning. However, it remains an open question whether existing methods and strategies can be adapted to unsupervised learning approaches.
Rollin Omari, Junae Kim, Paul Montague
doaj +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
Multi-Objective Unsupervised Feature Selection and Cluster Based on Symbiotic Organism Search
AlgorithmsUnsupervised learning is a type of machine learning that learns from data without human supervision. Unsupervised feature selection (UFS) is crucial in data analytics, which plays a vital role in enhancing the quality of results and reducing ...
Abbas Fadhil Jasim AL-Gburi +3 more
doaj +1 more source
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
, 1997 . A unified statistical learning approach called Bayesian YingYang (BYY) system and theory has been developed by the present author in recent years. This paper is the first part of a recent effort on systematically summarizing this theory. In this paper,
Semi-unsupervised Learning +5 more
core
Cell Consistency Evaluation Method Based on Multiple Unsupervised Learning Algorithms
Big Data Mining and AnalyticsUnsupervised learning algorithms can effectively solve sample imbalance. To address battery consistency anomalies in new energy vehicles, we adopt a variety of unsupervised learning algorithms to evaluate and predict the battery consistency of three ...
Jiang Chang +3 more
doaj +1 more source