Fruit Disease Detection Using Color,Texture and ANN
Objective
Our goal is to detect the fruit diseases by using OpenCV library, ANN model and K-means clustering method. Such an application is immensely useful in the field of farming and it is inexpensive for the user. We will also use image processing techniques for implementation.
Abstract
Rainfall prediction is the one of the important techniques to predict the climatic conditions in any country. This application proposes a rainfall prediction model using Multiple Linear Regression (MLR) for Indian dataset. The input data is having multiple meteorological parameters and to predict the rainfall in more precise. The Mean Square Error (MSE), accuracy, correlation are the parameters used to validate the proposed model. From the results, the proposed machine learning model provides better results than the other algorithms in the literature.
Keywords: Multiple Linear Regression, Rainfall, Prediction, Machine Learning, LSTM, RNN.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
HARDWARE SPECIFICATIONS:
- Processor: I3/Intel
- Processor RAM: 4GB (min)
- Hard Disk: 128 GB
- Key Board: Standard Windows Keyboard
- Mouse: Two or Three Button Mouse
- Monitor: Any
SOFTWARE SPECIFICATIONS:
- Operating System: Windows 7+
- Server-side Script: Python 3.6+
- IDE: PyCharm
- Libraries Used: Pandas,TensorFlow,Matplotlib,Numpy.
- Frame Works:Flask.
Learning Outcomes
- Scope of real time application scenarios.
- What is a search engine and how browser can work.
- What type of technology versions?
- Need of PyCharm-IDE to develop a web application.
- How to implement segmentation.
- Where this application can be used.
- What are the diseases attacked by the fruits.
- Features of OpenCV.
- Working Procedure.
- Testing Techniques.
- How to run and deploy the applications.
- Introduction to basic technologies.
- How project works.
- Input and Output modules.
- How test the project based on user inputs and observe the output.
- Project Development Skills:
- Problem analyzing skills.
- Problem solving skills.
- Creativity and imaginary skills.
- Programming skills.
- Deployment.
- Testing skills.
- Debugging skills.
- Project presentation skills.
- 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, not projects of or by IEEE.
