Results 101 to 110 of about 10,284,296 (292)

Material Coupling in Hybrid Neuromorphic Devices: From Fundamentals to System‐Level Applications

Advanced Functional Materials, EarlyView.
Hybrid neuromorphic devices utilize heterointerfaces between emerging semiconductors, where charge transfer and trapping, ion or defect modulation, and photogating are translated into synaptic functions. This paper discusses coupling strategies that tailor interfacial electronic and ionic properties in organic semiconductors, metal oxides, two ...
Minsu So, Sunwoo Jeong, Youngmin Han, Fabrizio Torricelli, Hocheon Yoo, Junhwan Choi   +5 more
wiley   +1 more source

Large Margin Few-Shot Learning

CoRR, 2018
The key issue of few-shot learning is learning to generalize. This paper proposes a large margin principle to improve the generalization capacity of metric based methods for few-shot learning. To realize it, we develop a unified framework to learn a more discriminative metric space by augmenting the classification loss function with a large margin ...
Yong Wang 0032, Xiao-Ming Wu 0003, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang 0006, Victor O. K. Li   +6 more
openaire   +3 more sources

Large margin meta-learning for few-shot classification [PDF]

, 2018
This paper proposes a large margin principle to overcome the problem of data scarcity in training meta-learning models for few-shot classification. To realize it, we develop an efficient framework that can be easily incorporated in existing metric-based ...
Wang, Y, Xiang, W, Li, VOK, Gu, J, Zhang, L, Wu, XM, Li, Q   +6 more
core  

Single‐Cell Resolution Mapping of Osteoarthritis‐Associated Chondrocyte Dynamics Using a High‐Density CMOS MEA Platform

Advanced Healthcare Materials, EarlyView.
Single‐cell and spatially resolved impedance mapping using a high‐density CMOS‐MEA platform enables non‐invasive monitoring of osteoarthritis‐associated chondrocyte dynamics. Continuous label‐free measurements reveal heterogeneous remodeling behaviors, including proliferation, migration, and phenotypic transitions, establishing a powerful approach for ...
Neha Deshpande, Pauline Coquart, Bram Theuns, Susanne Cremery, Jaime Rodolfo V. Garcia III, Julien Verplanken, Dennis Lambrechts, Dries Braeken, Liesbet Lagae, Johanna Bolander   +9 more
wiley   +1 more source

Few-shot cow identification via meta-learning

Information Processing in Agriculture
Cow identification is a prerequisite for precision livestock farming. Biometric-based methods have made significant progress in cow identification. However, substantial labelling costs and frequent identification task changes are still hamper model ...
Xingshi Xu, Yunfei Wang, Yuying Shang, Guangyuan Yang, Zhixin Hua, Zheng Wang, Huaibo Song   +6 more
doaj   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Few-Shot Learning with a Strong Teacher [PDF]

, 2022
Few-shot learning (FSL) aims to generate a classifier using limited labeled examples. Many existing works take the meta-learning approach, constructing a few-shot learner that can learn from few-shot examples to generate a classifier.
Ye, Han-Jia, Zhan, De-Chuan, Ming, Lu, Chao, Wei-Lun   +3 more
core   +1 more source

Learning to learn for few-shot continual active learning

Artificial Intelligence Review
AbstractContinual learning strives to ensure stability in solving previously seen tasks while demonstrating plasticity in a novel domain. Recent advances in continual learning are mostly confined to a supervised learning setting, especially in NLP domain.
Stella Ho, Ming Liu 0028, Shang Gao 0003, Longxiang Gao   +3 more
openaire   +4 more sources

Task Cooperation for Semi-Supervised Few-Shot Learning

, 2021
Training a model with limited data is an essential task for machine learning and visual recognition. Few-shot learning approaches meta-learn a task-level inductive bias from SEEN class few-shot tasks, and the meta-model is expected to facilitate the few ...
Li, Xin-Chun, Ye, Han-Jia, Zhan, De-Chuan   +2 more
core   +1 more source

Recent Progress in the Phase‐Controlled Synthesis of Ruthenium Nanocrystals for Catalytic Applications

Advanced Materials, EarlyView.
Template effect and kinetic control enable crystal‐phase engineering of Ru nanocrystals, granting access to either metastable fcc‐Ru or stable hcp‐Ru with distinct surface structures, thermal stabilities, and catalytic behaviors. Moreover, the hcp‐Ru can further serve as an epitaxial template to direct Pd and Rh nanocrystals into the metastable hcp ...
Jianlong He, Zhiqi Wang, Jiaqi Guan, Younan Xia   +3 more
wiley   +1 more source