2018年12月3日 · In recent years, deep network has shown its brilliant performance in many fields including feature extraction and projection. Therefore, in this paper, based on deep network and slow feature analysis (SFA) theory, we proposed a new change detection algorithm for multi-temporal remotes sensing images called Deep Slow Feature Analysis (DSFA).

2019年10月23日 · 本文介绍了一种新的变化检测算法DSFA，基于深度网络和慢特征分析理论，适用于多时相遥感图像。 DSFA通过两个对称的深度网络进行特征投影，利用SFA模块突出变化信息，并通过预检测和阈值算法确定变化区域。

Therefore, inspired by the idea of utilizing deep network learning non-linear transformations, we propose a new algo- rithm called Deep Slow Feature Analysis (DSFA) in this paper. In DSFA, two deep networks are used to extract and represent the features of remote sensing images obtained at different times, respectively.

To address the high costs associated with hardware-based monitoring, we introduced a novel hybrid model that synergizes dynamic slow feature analysis (DSFA), long short-term memory (LSTM) network, and convolutional block attention module (CBAM). The DSFA effectively resolves time lag issues prevalent in real industrial processes.

However, traditional algorithms often ignore the dynamic characteristics of actual industry process. This study proposes a novel algorithm called multistep dynamic slow feature analysis (MS-DSFA), which has completed the full-condition monitoring of a dynamic system and divided dynamic structures more precisely.

2018年3月22日 · 对于DSFA来说，它是应用开发商设计用于其所开发系统中业务流程处理的通用框架，它定义了15种业务行为，包括文件读写、数据库查询、循环、选择Java模块调用等方面，已经基本覆盖了大部分的业务行为。 因此具有一定的普适性，这也是我们为大家介绍的原因。

本文基于深度网络和慢特征分析（SFA）理论，提出了一种新的多时相遥感图像变化检测算法，即深度慢特征分析（DSFA）。 在DSFA模型中，两个对称深度网络用于投影双时相影像的输入数据。 然后，部署SFA模块以抑制不变的组件并突出显示已变换要素的已更改组件。 CVA预检测用于以高置信度找到未改变的像素作为训练样本。 最后，用卡方距离计算变化强度，并通过阈值算法确定变化。 实验是在两个真实世界的数据集和一个公共高光谱数据集上进行的。 视觉比较和定 …

2024年10月2日 · 本文将从DSFA框架的基本原理出发，通过渗透测试的视角，逐步深入挖掘DSFA框架中的漏洞，最终实现对业务系统的有效控制。 首先，DSFA框架是一个具有较强伸缩性和易配置的工作流处理框架，广泛应用于内部业务系统中，支持文件读写、数据库查询、循环、Java模块调用等常见业务行为。 通过反编译核心库文件，我们可以了解到框架的基本工作流程：用户传入的请求首先被DoPost Servlet接收，解析请求中的业务流程描述文件及参数，并传递给 …

Known for its breathtaking views and access to nature, the area is a haven for outdoor enthusiasts who enjoy kayaking, hiking, and exploring the lush riverfront trails. Rentals here cater to various lifestyles, with options for young professionals, families, and retirees.

In this paper, based on deep network and slow feature analysis (SFA) theory, we proposed a new change detection algorithm for multi-temporal remotes sensing images called Deep Slow Feature Analysis (DSFA). In DSFA model, two symmetric deep networks are utilized for projecting the input data of bi-temporal imagery.