Results 111 to 120 of about 514,020 (257)

Tibetan Few‐Shot Learning Model With Deep Contextualised Two‐Level Word Embeddings

CAAI Transactions on Intelligence Technology
Few‐shot learning is the task of identifying new text categories from a limited set of training examples. The two key challenges in few‐shot learning are insufficient understanding of new samples and imperfect modelling.
Ziyue Zhang, Yongbin Yu, Xiangxiang Wang, Xiao Feng, Yuze Li, Jiarun Shen, Dorje Tashi, Jin Zhang, Lobsang Yeshi, Lei Li, Nyima Tashi, Jingye Cai   +11 more
doaj   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Nanophotonic Strategies for Chiral Biosensing: Nanoparticles, Metasurfaces, Magneto‐Optical, and Quantum Approaches

Advanced Photonics Research, EarlyView.
Recent advances in nanophotonics‐based chiral biosensing approaches are comprehensively reviewed, highlighting key trends, advantages, and limitations of each technology. Special attention is given to emerging strategies that exploit magneto‐optical and quantum plasmonic phenomena to enhance sensitivity down to the level of a few molecules, or even a ...
Jorge Ricardo Mejía‐Salazar
wiley   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

Prompt-based learning for few-shot class-incremental learning

Alexandria Engineering Journal
Few-Shot Class-Incremental Learning (FSCIL) aims to enable deep neural networks to incrementally learn new tasks from a limited number of labeled samples, while retaining knowledge of previously learned tasks, mimicking the way humans learn.
Jicheng Yuan, Hang Chen, Songsong Tian, Wenfa Li, Lusi Li, Enhao Ning, Yugui Zhang   +6 more
doaj   +1 more source

Relational Generalized Few-Shot Learning

, 2019
Transferring learned models to novel tasks is a challenging problem, particularly if only very few labeled examples are available. Although this few-shot learning setup has received a lot of attention recently, most proposed methods focus on discriminating novel classes only.
Shi, Xiahan, Salewski, Leonard, Schiegg, Martin, Akata, Zeynep, Welling, Max   +4 more
openaire   +2 more sources

Vision‐Assisted Avocado Harvesting with Aerial Bimanual Manipulation

Advanced Robotics Research, EarlyView.
This work outlines the design and implementation of a bimanual aerial robot that employs visual perception and learning to detect, reach, and harvest avocados. A new gripper and fixer arm assembly is used to harvest avocados, while visual perception enables the detection of avocados and estimation of their position and orientation for determining ...
Zhichao Liu, Jingzong Zhou, Caio Mucchiani, Konstantinos Karydis   +3 more
wiley   +1 more source

Multi‐Material Additive Manufacturing of Soft Robotic Systems: A Comprehensive Review

Advanced Robotics Research, EarlyView.
This review explores the transformative role of multi‐material additive manufacturing (MMAM) in the development of soft robotic systems. It presents current techniques, materials, and design strategies that enable functionally graded and adaptive structures.
Ritik Raj, Quan‐Chen Song, Jia‐Yang Juang   +2 more
wiley   +1 more source

MetaChest: generalized few-shot learning of pathologies from chest X-rays

Visual Computing for Industry, Biomedicine, and Art
The limited availability of annotated data presents a major challenge in applying deep learning methods to medical image analysis. Few-shot learning methods aim to recognize new classes from only a few labeled examples.
Berenice Montalvo-Lezama, Gibran Fuentes-Pineda   +1 more
doaj   +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