Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Light Acquisition02:16

Light Acquisition

8.4K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.4K
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

273
Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
273
Chirality02:25

Chirality

23.0K
Chirality is a term that describes the lack of mirror symmetry in an object. In other words, chiral objects cannot be superposed on their mirror images. For example, our feet are chiral, as the mirror image of the left foot, the right foot, cannot be superposed on the left foot.
Chiral objects exhibit a sense of handedness when they interact with another chiral object. For example, our left foot can only fit in the left shoe and not in the right shoe. Achiral objects — objects that have...
23.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

microRNA-221 restricts human cytomegalovirus replication via promoting type I IFN production by targeting SOCS1/NF-κB pathway.

Cell cycle (Georgetown, Tex.)·2019
Same author

Hydrogen bonding derived self-healing polymer composites reinforced with amidation carbon fibers.

Nanotechnology·2019
Same author

Comparative analysis of the main active constituents from different parts of Leonurus japonicus Houtt. and from different regions in China by ultra-high performance liquid chromatography with triple quadrupole tandem mass spectrometry.

Journal of pharmaceutical and biomedical analysis·2019
Same author

The Comprehensive Evaluation of Safflowers in Different Producing Areas by Combined Analysis of Color, Chemical Compounds, and Biological Activity.

Molecules (Basel, Switzerland)·2019
Same author

The DNA-binding mechanism of the TCS response regulator ArlR from Staphylococcus aureus.

Journal of structural biology·2019
Same author

Two microporous Co<sup>II</sup>-MOFs with dual active sites for highly selective adsorption of CO<sub>2</sub>/CH<sub>4</sub> and CO<sub>2</sub>/N<sub>2</sub>.

Dalton transactions (Cambridge, England : 2003)·2019

相关实验视频

Updated: May 29, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.3K

花的分类方法整合了从前后两侧的深度视觉特征.

Yifan Chen1, Xichen Yang1, Hui Yan2,3

  • 1School of Computer and Electronic Information/School of Artificial Intelligence, Nanjing Normal University, Nanjing, Jiangsu, China.

Frontiers in plant science
|February 5, 2025
PubMed
概括

一种新的方法使用深度学习来通过融合前后图像特征来对花 (Chrysanthemum morifolium Ramat) 进行分类. 这种快速,非侵入性的技术达到93.8%的准确性,改善了草本作物的识别.

关键词:
花的分类 花的分类深度学习是一种深度学习.功能融合功能融合功能两个流网络网络的两个流.视觉信息是一种视觉信息.

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

455
Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection
07:04

Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection

Published on: March 10, 2021

3.9K

相关实验视频

Last Updated: May 29, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.3K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

455
Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection
07:04

Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection

Published on: March 10, 2021

3.9K

科学领域:

  • 农业科学 农业科学
  • 计算机视觉 计算机视觉
  • 生物技术是生物技术.

背景情况:

  • 兰花 (Chrysanthemum morifolium Ramat) 是一种有价值的中国草药作物,具有重要的药用用途.
  • 准确的分类和原产地识别对于生产者,消费者和市场监管至关重要.
  • 目前的识别方法是主观的,耗时的,需要昂贵的设备.

研究的目的:

  • 开发一种新的,快速的,非侵入性的,非接触的香分类和原产地识别方法.
  • 与现有方法相比,提高花识别的准确性和效率.

主要方法:

  • 图像预处理以消除背景噪声.
  • 一个双流深度学习网络,利用前后花图像.
  • 深度视觉特征的融合使用单流和交叉流的残余连接.

主要成果:

  • 拟议的方法实现了93.8%的分类准确度.
  • 该方法表现出卓越的稳定性,并优于现有的识别方法.
  • 该方法为花的识别提供了有效和可靠的解决方案.

结论:

  • 开发的深度学习方法为香的分类和原产地识别提供了有效和准确的解决方案.
  • 这种技术在农业生产和市场的质量保证方面具有实际好处.
  • 该研究为有关草本作物的监管过程提供了有价值的工具.