Results 1 to 10 of about 11,802,626 (213)

A novel heuristic target-dependent neural architecture search method with small samples [PDF]

Frontiers in Plant Science, 2022
It is well known that crop classification is essential for genetic resources and phenotype development. Compared with traditional methods, convolutional neural networks can be utilized to identify features automatically. Nevertheless, crops and scenarios
Leiyang Fu, Leiyang Fu, Shaowen Li, Shaowen Li, Yuan Rao, Yuan Rao, Jinxin Liang, Jinxin Liang, Jie Teng, Jie Teng, Quanling He, Quanling He   +11 more
doaj   +2 more sources

Attention-Guided Residual Spatiotemporal Network with Label Regularization for Fault Diagnosis with Small Samples [PDF]

Sensors
Fault diagnosis is of great significance for the maintenance of rotating machinery. Deep learning is an intelligent diagnostic technique that is receiving increasing attention.
Yanlong Xu, Liming Zhang, Ling Chen, Tian Tan, Xiaolong Wang, Hongguang Xiao   +5 more
doaj   +2 more sources

Feature Ranking on Small Samples: A Bayes-Based Approach [PDF]

Entropy
In the modern world, there is a need to provide a better understanding of the importance or relevance of the available descriptive features for predicting target attributes to solve the feature ranking problem.
Aleksandra Vatian, Natalia Gusarova, Ivan Tomilov   +2 more
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Learning General-Purpose Representations for Cross-Domain Hyperspectral Images Classification with Small Samples

Remote Sensing, 2023
Cross-domain classification with small samples is a more challenging and realistic experimental setup. Until now, few studies have focused on the problem of small-sample cross-domain classification between completely different hyperspectral images (HSIs)
Kuiliang Gao, Anzhu Yu, Xiong You, Chunping Qiu, Bing Liu, Wenyue Guo   +5 more
doaj   +1 more source

Classification method based on Taguchi’s T-method for small sample sizes

Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2021
This paper proposes a classification method using Taguchi’s T-method. Collecting sufficient number of training samples at the initial stage of production and at the beginning of the development process is difficult.
Keisuke NISHINO, Arata SUZUKI, Daisuke FUJITA   +2 more
doaj   +1 more source

CGC-NET: Aircraft Detection in Remote Sensing Images Based on Lightweight Convolutional Neural Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
In the past few years, aircraft detection in remote sensing (RS) images has been an important research hotspot, and it is very crucial in plenty of military applications.
Ting Wang, Xiaodong Zeng, Changqing Cao, Wei Li, Zhejun Feng, Jin Wu, Xu Yan, Zengyan Wu   +7 more
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Study on Small Samples Active Sonar Target Recognition Based on Deep Learning

Journal of Marine Science and Engineering, 2022
Underwater target classification methods based on deep learning suffer from obvious model overfitting and low recognition accuracy in the case of small samples and complex underwater environments.
Yule Chen, Hong Liang, Shuo Pang
doaj   +1 more source

Optimizable Image Segmentation Method with Superpixels and Feature Migration for Aerospace Structures

Aerospace, 2022
The lack of high-quality, highly specialized labeled images, and the expensive annotation cost are always critical issues in the image segmentation field. However, most of the present methods, such as deep learning, generally require plenty of train cost
Chengwei Fei, Jiongran Wen, Lei Han, Bo Huang, Cheng Yan   +4 more
doaj   +1 more source

An Easy-to-Use Histological Technique for Small Biological Samples of Senegalese Sole Larvae

Applied Sciences, 2023
Histological techniques are a traditional and essential tool for adequately comprehending cellular morphology and physiology in several scientific fields, including ecotoxicological studies.
Lígia M. B. M. Santana, Évila Pinheiro Damasceno, Susana Loureiro, Amadeu M. V. M. Soares, Pedro Pousão-Ferreira, Denis M. S. Abessa, Roberto Martins, Maria D. Pavlaki   +7 more
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Multi-criteria neural network estimation of correlation coefficients for processing small samples of biometric data

Известия высших учебных заведений. Поволжский регион:Технические науки, 2021
Background. Over 120 years, Pearson’s criterion has been widely used to calculate correlation coefficients. Unfortunately, its use generates significant errors in calculating the correlation coefficients on small samples.
A.I. Ivanov, Yu.I. Serikova, T.A. Zolotareva, S.A. Polkovnikova   +3 more
doaj   +1 more source