Results 91 to 100 of about 167,467 (260)
Abstract A central concern of machine learning is overfitting—which occurs when a prediction model includes too many explanatory variables and predicts noise. The problem with overfitting is that it leads the model to poorer out-of-sample predictions because it misattributes causal significance to irrelevant variables. We argue that a
Ian Ayres, Yair Listokin
openaire +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
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
Delving into Unsupervised Hebbian Learning from Artificial Intelligence Perspectives
Unsupervised Hebbian learning is a biologically inspired algorithm designed to extract representations from input images, which can subsequently support supervised learning.
Wei Lin +2 more
doaj +1 more source
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
Adjusted Overfitting Regression
In this paper, I will introduce a new form of regression, that can adjust overfitting and underfitting through, "distance-based regression." Overfitting often results in finding false patterns causing inaccurate results, so by having a new approach that minimizes overfitting, more accurate predictions can be derived.
openaire +2 more sources
Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling
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
Intelligent Sky Guardians (InSkyGuard) is introduced as a four‐drone swarm that autonomously detects, tracks, and safely captures rogue drones using a coordinated net system. Computer vision and leader–follower control architecture enable synchronized enclosure, while integrated failsafes enhance system reliability. Validated through closed‐environment
Joshua Hastings +6 more
wiley +1 more source
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
A Novel Supervised Learning Based on Density
– Because prototype based classifiers are both easy and reasonable methods, there have been many studies on similarity based supervised learning. In order to detect each class region, they should not only appropriately locate the prototypes, but also ...
Umut Orhan, Mahmut Hekim
doaj

