Enhancement of classification accuracy of multi-spectral satellites’ images using Laplacian pyramids

Serwa, A.; Elbialy, Samy

doi:10.1016/j.ejrs.2020.12.006

Cited by 7 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The same problem can be found, it is temporally faraway from now and a lot of achievements are reached e.g. Serwa (Serwa, 2009(Serwa, , 2017a(Serwa, , 2017bSerwa & Elbialy, 2020), who enhanced the performance of ANN step by step by monitoring the errors between the neurons of input layer, hidden layers and output layer of multi-layer perceptron (MLP). Sachdeva et al ( 2016) developed the package -SFERCB -"Segmentation, feature extraction, reduction, and classification analysis by both SVM and ANN for brain tumors.…”

mentioning

confidence: 83%

Development of Soft Computational Simulator for Optimized Deep Artificial Neural Networks for Geomatics Applications: Remote Sensing Classification as an Application

Serwa

2022

Geodesy and Cartography

Self Cite

View full text Add to dashboard Cite

Artificial neural networks (ANN) obtain more importance after the innovation of deep learning (DL) approach. This research is oriented towards development of soft computational simulator for geomatics research using ANN supporting the deep approach. ANN seems to be a black box due to its sensitivity towards initialization, architecture, and behavior. This research gives a spotlight on the dull areas of ANN algorithm by developing a soft computational simulator for it. The applied examples are chosen to cover geomatics data. DANNDO (Deep Artificial Neural Networks Designer and Optimizer) software is developed to achieve the research objective. Multi-layer perceptron (MLP) architecture is applied in this simulator. Geomatics (remote sensing multi- spectral data) is selected to be a testing paradigm to insure the reliability of the developed simulator. The developed simulator proved the high performance of applying both shallow and deep ANN (DANN).

show abstract

mentioning

confidence: 83%

Development of Soft Computational Simulator for Optimized Deep Artificial Neural Networks for Geomatics Applications: Remote Sensing Classification as an Application

Serwa

2022

Geodesy and Cartography

Self Cite

View full text Add to dashboard Cite

show abstract

“…At the slave station (robot arm control terminal), motion control and environmental information acquisition are primarily accomplished based on the ROS (Robot Operating System) for robots. ROS is a highly flexible software architecture designed for writing robot software programs [8]. It encompasses a wide range of tools, library code, and standardized protocols, with the aim of simplifying the challenges and complexities of creating intricate and robust robot behavior across various robot platforms.…”

Section: Overall System Planningmentioning

confidence: 99%

Research on vision control methods based on multi-sensor fusion

Wang,

Qu,

Wang

et al. 2024

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

This paper focuses on the application scenarios of electric power live line working robots, addressing tasks such as live wire stripping and live wire connection/disconnection. It utilizes Mixed Reality (MR) technology for rapid environment modeling and visual signal acquisition. Through the research on robot contact force sensing, real-time force feedback, and obstacle avoidance through the fusion of robot motion paths and environmental data, it establishes a novel electric power live line working robot system centered around dexterous dual arms at the operation end, force feedback teleoperation controllers, multi-sensor fusion acquisition systems, and robot motion planning and control technology. Through prototyping, a demonstration application is realized, showcasing a semi-autonomous electric power live line working robot system that employs remote operation combined with sensor-based MR for task execution. This teleoperation and Mixed Reality-based semi-autonomous electrified operation approach is poised to play a significant role in advancing and demonstrating the use of robots in the field of electrical grid operations.

show abstract

“…This involves a specialized dual-arm robot body and a remote dexterous control system, incorporating technologies like special reducers and multidimensional force sensors to enhance key technical indicators such as dexterity, ease of use, and load capacity. The goal is to match or exceed international advanced levels [10] .…”

Section: Technical Research and Comparative Analysismentioning

confidence: 99%

Research on the design of remote avatar robot based on mixed reality and teleoperation

WANG,

Qu,

Wang

et al. 2024

Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023)

View full text Add to dashboard Cite

This paper examines the global development of intelligent robots, focusing on remote avatar robots. Some key technologies are researched such as mixed reality and teleoperation by analyzing their status, trends, and challenges. Theoretical background and technical solutions for remote avatar robots are explored, covering hardware and software aspects. A new intelligent robot system for hot-line working with flexible arms, force feedback teleoperation controller and mixed reality technology is established. The robot system in the air can fulfill the working like the wire stripping and removal by human teleoperating with mixed reality scene in the ground, meanwhile a security system of UAV with full perception monitoring and active intervention is cooperated in the air. In the end, the article proposes a prototype design integrating teleoperation, mixed reality, and 5G communication for live working in 10KV high-voltage environments, validated through experiments.

show abstract

Enhancement of classification accuracy of multi-spectral satellites’ images using Laplacian pyramids

Cited by 7 publications

References 13 publications

Development of Soft Computational Simulator for Optimized Deep Artificial Neural Networks for Geomatics Applications: Remote Sensing Classification as an Application

Development of Soft Computational Simulator for Optimized Deep Artificial Neural Networks for Geomatics Applications: Remote Sensing Classification as an Application

Research on vision control methods based on multi-sensor fusion

Research on the design of remote avatar robot based on mixed reality and teleoperation

Contact Info

Product

Resources

About