Results 81 to 90 of about 6,372,670 (283)

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

Bayesian Ying-Yang System and Theory as a Unified Statistical Learning Approach (I): for Unsupervised and Semi-Unsupervised Learning

, 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, Lei Xu, For Unsupervised, S. Amari, N. Kassabov, An Invited Book Chapter   +5 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

Multi-Objective Unsupervised Feature Selection and Cluster Based on Symbiotic Organism Search

Algorithms
Unsupervised 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, Mohd Zakree Ahmad Nazri, Mohd Ridzwan Bin Yaakub, Zaid Abdi Alkareem Alyasseri   +3 more
doaj   +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, Eran Beeri Bamani, Joao Buzzatto, Bryan Busby, Lucas Ferrari Gerez   +4 more
wiley   +1 more source

Cell Consistency Evaluation Method Based on Multiple Unsupervised Learning Algorithms

Big Data Mining and Analytics
Unsupervised 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, Xianglong Gu, Jieyun Wu, Debu Zhang   +3 more
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

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

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, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source