Results 111 to 120 of about 10,284,296 (292)

Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization

Complex & Intelligent Systems
Few-shot learning has achieved great success in recent years, thanks to its requirement of limited number of labeled data. However, most of the state-of-the-art techniques of few-shot learning employ transfer learning, which still requires massive ...
Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su   +5 more
doaj   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Few-Shot Object Detection via Baby Learning [PDF]

, 2022
Few-shot learning is proposed to overcome the problem of scarce training data in novel classes. Recently, few-shot learning has been well adopted in various computer vision tasks such as object recognition and object detection.
Nguyen, Tam, Vu, Anh-Khoa Nguyen, Nguyen, Khanh-Duy, Nguyen, Vinh-Tiep, Ngo, Thanh Duc, Do, Thanh-Toan, Nguyen, Nhat-Duy   +6 more
core   +1 more source

Advances in Bio‐Integrated Edge Computing Systems for Smart and Connected Health

Advanced Materials, EarlyView.
This review explores advances in bio‐integrated edge computing for healthcare, focusing on co‐designing computing, sensing, and energy strategies to overcome integration and power challenges for optimized, decentralized operation. ABSTRACT Recent advances in bio‐integrated healthcare technologies have enabled continuous, high‐resolution monitoring and ...
Gyuwon Kim, Seungwon Yoo, Tae Woog Kang, Yunuo Huang, Woon‐Hong Yeo   +4 more
wiley   +1 more source

Biomass DNA: An Emerging Building Block for Advanced Materials

Advanced Materials, EarlyView.
Biomass DNA is rapidly emerging from its traditional role as a genetic blueprint to serve as a versatile abundant, highly programmable polymeric building block. This review highlights the transformation of macroscopic bulk biomass DNA into next generation of functional materials, spanning from dynamic hydrogels, sustainable bioplastics, and high ...
Yuwei Hu, Itamar Willner, Li Niu
wiley   +1 more source

Few-Shot Learning Method with Augmentation Data Based on Transferring Intra-Class Variations [PDF]

Jisuanji gongcheng
Few-shot learning aims to classify new categories based on only one or a few examples. To address this problem, data augmentation is often used as a direct and effective approach. Further, the augmented data should be diverse and discriminable.
LI Xiaoyu, LUO Na
doaj   +1 more source

Blending With Insulating Polymers Enables Stable Anti‐Ambipolar Characteristics in n‐Type Organic Mixed‐Conductors for Heterogeneous Spiking Neurons

Advanced Materials, EarlyView.
A polymer blend of n‐type OMIEC P(gNDI‐gT2) with insulating PMMA yields mechanically stabilized, anti‐ambipolar organic electrochemical transistors (OECTs) with tunable ionic‐electronic transport. This blending allows low‐power, fast‐spiking heterogeneous Hodgkin–Huxley neurons, enabling biomimetic frequency deconvolution and reservoir computing, which
Zachary Laswick, Ariel Lifer, Catherine Beaumont, Liad Hayoun, Priscila Cavassin, Zeinab Hamid, Dilara Meli, William Dupont, Lincoln J. Lauhon, Iain McCulloch, Gitti L. Frey, Giovanni Maria Matrone, Jonathan Rivnay   +12 more
wiley   +1 more source

GlocalDualNet: Disentangling Scale and Representation for Few-Shot Remote Sensing Segmentation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
The core task of semantic segmentation is to assign predefined category labels to each pixel in an image, thereby distinguishing between different objects and backgrounds.
Hengren Tang, Yaxuan Jia, Jiacheng Cheng, Yang Mu, Yi Wu, Xiwen Yao   +5 more
doaj   +1 more source

Low Resistance Interphase Formation at the PEO‐LiTFSI|LGPS Interface in Lithium Solid‐State Batteries

Advanced Materials Interfaces, EarlyView.
Interfacial charge transfer and low‐resistance interphase formation between PEO‐based polymer and Li10GeP2S12 solid electrolytes are investigated using multi‐electrode impedance spectroscopy and advanced analytical techniques such as XPS and ToF‐SIMS.
Ujjawal Sigar, Timo Weintraut, Sebastian L. Benz, Semih Engün, Sascha Kremer, Anja Henss, Felix H. Richter   +6 more
wiley   +1 more source

Few-shot learning using generative modeling [PDF]

, 2018
In many machine learning tasks, the available training data has a skewed distribution- a small set of training classes for which a large number of examples are available (“base classes”), and many classes for which only a limited number of examples are ...
Hegde, Narayan, Toshev, Alexander, Leung, King Hong, Movshovitz-Attias, Yair   +3 more
core   +1 more source