Paper PublishingDesign and Implementation of a Cloud Particle Shape Recognition Algorithm Based on MATLAB
Objective
The primary objective of this project is to develop a robust and efficient cloud particle shape recognition algorithm using MATLAB. This algorithm will analyze images or data of cloud particles and classify them based on their shapes, contributing to a deeper understanding of atmospheric processes and aiding in meteorological research.
Abstract
Clouds are an important factor affecting climate change and the cloud microphysical characteristics are an important aspect to describe the cloud. Airborne two-dimensional stereo probe detector (2D-S) is widely used in domestic meteorological observation for the cloud microphysics research. Aiming at the situation that cloud particle shape classification based on artificial naked eye is not only subjective and different, but also time-consuming and poor in classification effect, a cloud particle shape recognition method based on convolution neural network (CNN) is proposed. A 21-layer convolutional neural network model is built by using a lightweight convolution module to realize the automatic shape recognition of cloud particle shapes.
Keywords-component; cloud particles; shape recognition; convolutional neural network; 2D-S
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
