Results 61 to 70 of about 5,573 (153)
Fujian Economic Forecasting Based on Deep Belief Network —Consumer price index and total imports prediction in fujian province as an example [PDF]
, 2017 对宏观经济走势做出准确的预测，对于分析宏观调控政策的得失、评价经济系统运行的质量和正确制定未来发展规划战略等具有重要的意义。本文将近年来机器学习领域备受关注的深度置信网络（DeepBeliefNetwork，DBN）引入到经济预测领域，用于解决传统BP(Backpropagation)人工神经网络经济预测方法所存在的问题，例如训练学习速度较慢、容易陷入局部极小、容易导致过拟合、泛化能力差等不足，使得神经网络方法在经济预测领域焕发新的生机。 本文首先介绍了经济预测的研究背景和现状。其次介绍了经济预测特点 ...
王敏
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Child Rights Impact Assessment: A Policy Tool for a Rights‐Respecting Digital Environment
Policy &Internet, Volume 17, Issue 3, September 2025.ABSTRACT Businesses that develop digital products and services often anticipate generic users, paying insufficient attention to the needs and rights of children who may use or be impacted by their practices. This article investigates the potential of child rights impact assessment (CRIA) as a policy tool to protect and respect children's rights in the ...
Sonia Livingstone, Kruakae Pothong
wiley +1 more source
A Deep Learning Pan-sharpening Method Driven by Domain Knowledge [PDF]
, 2017 Pan-sharpening是将同一场景的全色（PAN）图像和多光谱（MS）图像相互融合以有效提高MS图像的空间分辨率。Pan-sharpening在无需升级硬件的情况下有效克服了单一传感器的物理局限性，因而成为遥感领域的研究热点，并已广泛应用于自然资源探测、环境监测、军事侦察、和灾害监控等领域。 Pan-sharpening的主要目标是在光谱基本不失真的前提下尽可能提高MS图像的空间分辨率，其中MS图像具有较高的谱分辨率但是空间分辨率较低，PAN图像则具有很高的空间分辨率但缺少光谱分辨能力 ...
胡宇雯
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International Journal of Applied Linguistics, Volume 35, Issue 3, Page 1482-1494, August 2025.ABSTRACT While previous research has established nominal complexity as a key indicator of grammatical complexity, its multi‐dimensional manifestation in constrained varieties remains underexplored. This study investigates the distribution of complex nominal structures in constrained spoken English varieties, specifically English as a Second Language ...
Jiaxin Chen, Yao Yao, Dechao Li
wiley +1 more source
New Phytologist, Volume 247, Issue 3, Page 1460-1473, August 2025.Summary Podocarpus pollen morphology is shaped by both phylogenetic history and the environment. We analyzed the relationship between pollen traits quantified using deep learning and environmental factors within a comparative phylogenetic framework.
Marc‐Élie Adaimé +4 more
wiley +1 more source
, 2018 针对物体检测实时多目标回归算法中分别优化各四个位置参数,割裂了四个位置变量之间的关系,造成对物体的边框回归不够准确且训练不易收敛的问题,提出一种带检测评价函数(Intersection over Union,IoU)作为损失函数的实时多目标回归人脸检测算法。首先基于Redmond等提出实时多目标回归模型,采用该模型检测实时性的机制,然后融合了IoU函数作为位置参数的损失函数,将实时多目标回归模型中的四个独立位置参数整合成一个单元进行优化,避免了基础模型的缺陷。算法在人脸检测基准库FDDB上进行测试 ...
卓勇, 吴志洋, 廖生辉
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Review of Deep Learning Applications in Unmanned Aerial Vehicle Remote Sensing Images of Grass Plants [PDF]
The invasion of grass species competes for resources necessary for the growth of crops, significantly affecting crop yield and quality. Grasses such as the Artemisia genus release allergenic pollen, causing allergic reactions and impacting human health ...
LI Shaobo, WANG Xiaoqiang, GUO Libiao, HONG Ying, WANG Zhiguo
core +1 more source
China's Eco‐Civilisation, Climate Leviathan, and Hobbesian Energy Transition
Antipode, Volume 57, Issue 3, Page 830-861, May 2025.Abstract Scholars have hitherto tended to theorise China's ecological civilisation project either as a form of environmental authoritarianism or as a vision of eco‐socialism. This paper contributes to the conversation by conducting a textual analysis of Chinese scholarly discussions on eco‐civilisation.
David Chen
wiley +1 more source
Research on Sentiment Annotation and Analysis of GIF videos in Social Network [PDF]
, 2016 近年来随着社交网络的快速发展，GIF视频正在占据日益重要的地位。据我们从新浪微博中获取到的数据，15.1%的微博中含有GIF视频内容，其中超过九成的GIF内容是用来表达发送者的情感。研究GIF视频的情感倾向性，不仅可以推动动态时序视觉内容的理解与分析，具有重要的理论意义，同时可以帮助政府或公司了解网民对舆论热点事件的态度，从而提供决策支持，具有实际的应用价值。 GIF视频的情感倾向性分析是一项很有挑战性的工作，其主要包括两个核心问题，第一个核心问题是如何确定哪些GIF视频中的概念语义需要被处理 ...
蔡政
core
Research on mimic decision method based on deep learning [PDF]
Due to software and hardware differentiation, the problem of false positives mistakenly identified as network attack behavior caused by inconsistent mimic decision results frequently occurs.Therefore, a mimic decision method based on deep learning was ...
Bing HAO +4 more
core +1 more source