农业联邦学习的审查
Krista Rizman Žalik1,2, Mitja Žalik1
1Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia.
Sensors (Basel, Switzerland)
|December 9, 2023
概括
联合学习 (FL) 通过在边缘设备上培训模型而提高智能农业,而无需共享原始数据. 本综述详细介绍了农业问题解决的FL应用,方法和架构.
科学领域:
- 农业科学 农业科学
- 计算机科学 计算机科学
- 机器学习 机器学习
背景情况:
- 联合学习 (FL) 允许对分散数据进行模型培训,这对于保护隐私的农业管理至关重要.
- 智能农业依赖于先进的分析以提高效率,但数据隐私问题往往限制了集中式方法.
研究的目的:
- 提供农业中联合学习应用的全面审查.
- 分析农业环境中使用的各种FL技术,架构和数据分区策略.
- 提供FL在智能农业方面的进展和沟通解决方案的概述.
主要方法:
- 对农业中联合学习的现有文献进行系统审查.
- 对不同FL类型 (水平,垂直,混合) 和数据分区的比较分析.
- 检查集中式与去中心化的架构以及跨设备与跨 silo 联合层面.
- 综合算法和沟通策略的审查,在农业的FL使用.
主要成果:
- 确定了FL在各种农业挑战中的多种应用.
- 基于数据分区,架构和联合级别的不同FL方法进行了比较.
- 总结了在审查的FL研究中使用聚合算法和通信解决方案的情况.
- 突出了FL采用智能农业的进展和趋势.
结论:
- 联合学习提供了一个强大的框架,通过保护隐私的数据分析来推进智能农业.
- 了解FL类型,架构和算法的细微差别是成功在农业中实施的关键.
- 本综述为研究人员和从业人员在将FL应用于农业问题的过程中提供了宝贵的见解.
相关概念视频
02:16Light Acquisition
8.5K
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.
8.5K
01:27Associative Learning
399
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Classical conditioning, also known...
399
01:25Multiple Regression
3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
02:41Responses to Drought and Flooding
10.7K
Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.
10.7K
01:29Aggregates Classification
327
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
327