Results 91 to 100 of about 601,753 (327)
Semi-Supervised Phoneme Recognition with Recurrent Ladder Networks
, 2017 Ladder networks are a notable new concept in the field of semi-supervised learning by showing state-of-the-art results in image recognition tasks while being compatible with many existing neural architectures.
Alpay, Tayfun +3 more
core +1 more source
, 2017 Semi-supervised learning deals with the problem of how, if possible, to take advantage of a huge amount of not classified data, to perform classification, in situations when, typically, the labelled data are few. Even though this is not always possible (it depends on how useful is to know the distribution of the unlabelled data in the inference of the ...
Cholaquidis, Alejandro +2 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.A dual‐gradient centrifugal microfluidic platform enables ultrafast, high‐throughput screening of nanomaterials in 90 reaction chambers. Through siphon‐based aliquoting and automated gradient generation, the system achieves combinatorial synthesis of silver nanoparticles with diverse morphologies.
Hiep Van Nguyen +2 more
wiley +1 more source
Active learning for deep object detection by fully exploiting unlabeled data
Connection Science, 2023 Object detection is a challenging task that requires a large amount of labeled data to train high-performance models. However, labeling huge amounts of data is expensive, making it difficult to train a good detector with limited labeled data.
Feixiang Tan, Guansheng Zheng
doaj +1 more source
Asymptotic Analysis of Generative Semi-Supervised Learning [PDF]
, 2010 Semisupervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likelihood we quantify the asymptotic accuracy of generative semi-supervised ...
Balasubramanian, Krishnakumar +2 more
core +1 more source
Future Frontiers in Bioinspired Implanted Biomaterials
Advanced Materials, EarlyView.Gu et al. present an integrative overview of cutting‐edge strategies in bioinspired implantable biomaterials for organ regeneration, highlighting how emerging approaches—including 3D bioprinting, scaffold design, hydrogel systems, surface modification, nanofiber engineering, and genetic manipulation—converge to restore structure and function across ...
Qi Gu +3 more
wiley +1 more source
Semi-supervised Classification Based Mixed Sampling for Imbalanced Data
Open Physics, 2019 In practical application, there are a large amount of imbalanced data containing only a small number of labeled data. In order to improve the classification performance of this kind of problem, this paper proposes a semi-supervised learning algorithm ...
Zhao Jianhua, Liu Ning
doaj +1 more source
Néel Tensor Torque in Polycrystalline Antiferromagnets
Advanced Materials, EarlyView.This work introduces a Néel tensor torque based on a rank‐two symmetric tensor capturing spin correlations in a polycrystalline antiferromagnet. It shows the Néel tensor can be shaped and reshaped through the spin‐orbit torque (SOT) technique, enabling field‐free SOT switching with a specific polarity of the adjacent ferromagnet. This discovery opens a
Chao‐Yao Yang +4 more
wiley +1 more source
Graph regularized low-rank representation for semi-supervised learning
Journal of Algorithms & Computational Technology, 2021 Low-rank representation (LRR) has attracted wide attention of researchers in recent years due to its excellent performance in the exploration of high-dimensional subspace structures.
Cong-Zhe You +3 more
doaj +1 more source
Semi-supervised Learning based on Distributionally Robust Optimization
, 2019 We propose a novel method for semi-supervised learning (SSL) based on data-driven distributionally robust optimization (DRO) using optimal transport metrics.
Balsubramani A. +12 more
core +1 more source