Results 61 to 70 of about 740 (176)

FSIF-PCNN: A physics-constrained neural network for full-spectrum solar-induced chlorophyll fluorescence reconstruction

open access: yesInternational Journal of Applied Earth Observations and Geoinformation
Full-spectrum solar-induced chlorophyll fluorescence (SIF; 650–800 nm) provides a powerful means to characterize vegetation functional status. However, current retrieval methods still exhibit substantial uncertainties due to their reliance on fixed ...
Dianrun Zhao   +4 more
doaj   +1 more source

Construction and application of PPCNN model in evaluating sustainable utilization for regional water and soil resources——taking Sanjiang Plain in China as a case(区域水土资源可持续利用评价的脉冲耦合神经网络(PCNN)模型模糊算法的构建与应用)

open access: yesZhejiang Daxue xuebao. Lixue ban, 2009
针对三江平原水土资源区域特点,选择了 20个指标,建立了水土资源评价指标体系和标准;对脉冲耦合神经网络模型(PCNN模型)进行了改进,提出基于模糊算法的F-PCNN模型,动态阈值等于区域水土资源评价标准的等级范围,省略了不必要的参数,减少了模型的复杂度,并应用于三江平原水土资源评价中.分析结果表明三江平原创业农场水土资源可持续利用评价等级为II级,说明水土资源开发和利用较合理,可持续发展能力较强.应用结果说明F-PCNN模型在三江平原水土资源可持续利用评价中是可行的,既拓展了 PCNN的应用领域 ...
SUAn-yu(苏安玉)   +3 more
doaj   +1 more source

Image retrieval based on colour and improved NMI texture features

open access: yesAutomatika, 2019
This paper proposes an improved method for extracting NMI features. This method uses Particle Swarm Optimization in advance to optimize the two-dimensional maximum class-to-class variance (2OTSU) in advance.
Anyu Du, Liejun Wang, Jiwei Qin
doaj   +1 more source

A New Cooperative Anomaly Detection Method for Stacker Running Track of Automated Storage and Retrieval System in Industrial Environment

open access: yesJournal of Control Science and Engineering, 2018
Considering the complexity and the criticality of the stacker equipment, in order to solve the problem that the stop accuracy of the stacker reduces or even fails to work due to abrasion of the running rail, this paper proposes a cooperative detection ...
Darong Huang   +3 more
doaj   +1 more source

A New Pulse Coupled Neural Network (PCNN) for Brain Medical Image Fusion Empowered by Shuffled Frog Leaping Algorithm

open access: yesFrontiers in Neuroscience, 2019
Recent research has reported the application of image fusion technologies in medical images in a wide range of aspects, such as in the diagnosis of brain diseases, the detection of glioma and the diagnosis of Alzheimer’s disease.
Chenxi Huang   +7 more
doaj   +1 more source

Multimodal Fusion Hybrid Attention Parallel Deep Learning for Avocado Ripeness Classification

open access: yesIEEE Access
A significant challenge with climacteric fruits is that the ripening process will start after being harvested from the tree. This has led to frequent unintentional misjudgments of ripeness, significantly affecting retailers and consumers worldwide.
Sumitra Nuanmeesri
doaj   +1 more source

Physics-constrained neural networks for reliable solar power forecasting with uncertainty quantification

open access: yesResults in Engineering
While accurate forecasting with uncertainty estimation is highly important, Machine Learning (ML) and Deep Learning (DL) models often ignore fundamental physical principles and typically do not provide reliable uncertainty estimates.
Rajaperumal T. A   +1 more
doaj   +1 more source

Optimization of image restoration technology and AI iterative upgrade based on PCNN

open access: yesScientific Reports
This study aims to enhance the overall balance among image detail restoration, structure preservation, and model adaptability in image restoration tasks.
Bingxuan Zhang, Xuan Chen
doaj   +1 more source

改进型PCNN在绝缘子图像分割中的应用

open access: yesDianci bileiqi, 2013
针对高压输电线路绝缘子状态检测中光照不均匀、对比度不强的红外绝缘子图像分割,提出了一种基于类内绝对差准则的改进型PCNN图像分割算法。对最小类内绝对差法进行改进,引入背景与目标的面积差因子,确定最佳分割阈值后通过PCNN算法迭代优化进行图像分割。与经典OTSU算法、基于最小类内绝对差准则的PCNN算法进行比较。实验结果表明,本文方法能够取得更好的分割效果,并且具有较强的实用性。
徐雪涛   +3 more
doaj  

P-CNN: Percept-CNN for semantic segmentation

open access: yesComputer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
The task of image segmentation remains a fundamental challenge, in the field of computer vision. Convolutional Neural Networks (CNNs) have achieved significant success in this field, yet there are some limitations in the conventional approach.
Deepak Hegde, G. N. Balaji
doaj   +1 more source

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