Results 131 to 140 of about 452,378 (262)
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
Three types of incremental learning. [PDF]
van de Ven GM, Tuytelaars T, Tolias AS.
europepmc +1 more source
Speaker Identification Based on Incremental Learning Neural Network [PDF]
Kwang-Seung Heo, Kwee-Bo Sim
openalex +1 more source
TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications
TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince +3 more
wiley +1 more source
Task-Incremental Learning for Drone Pilot Identification Scheme. [PDF]
Han L, Zhong X, Zhang Y.
europepmc +1 more source
When Does the Incremental Risk Format Aid Informed Medical Decisions? The Role of Learning, Feedback, and Number of Treatment Options [PDF]
Kevin E. Tiede +3 more
openalex +1 more source
A miniaturized soft optical sensor that uses thin film color tuning enables real‐time 3D shape‐sensing from a single red–green–blue (RGB) signal. When integrated into a soft robot, it enables closed‐loop control and autonomous navigation in a phantom lung environment without the need for onboard electronics, achieving sub‐millimeter accuracy through ...
Frank Juliá Wise +6 more
wiley +1 more source
Incremental Learning for Online Data Using QR Factorization on Convolutional Neural Networks. [PDF]
Kim J, Lee W, Baek S, Hong JH, Lee M.
europepmc +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

