SRS Implementation of Deep Learning Approach for detection of Plant Leaf Diseases

Early detection of Plant diseases can improve the growth of plants and yield production. It is complicated and expensive to detect on manual basis detection regularly by domain experts and it will not give accurate prediction. Artificial intelligence techniques are better approach to automatic plant disease detection and diagnosis with highly accurate results.The program will be implemented to detect the Plant leaf Diseases by using deep learning methods such as classification of different healthy and disease plant leaves. In this system, it will be considered requirements that utilize Plant leaf images repository datasets for experimentation.

Scope of Project Implementation of Deep Learning Approach for detection of Plant Leaf Diseases:

Project scope is the part of project planning that involves determining and documenting a list of specific project  goals, deliverables, tasks, costs and deadlines. Defining the project scope involves adopting a clear vision and an agreement on the outcomes of the project. This allows each milestone of the project to stay on target

Functional and Non Functional Requirements of Implementation of Deep Learning Approach for detection of Plant Leaf Diseases:

Functional Requirements of Implementation of Deep Learning Approach for detection of Plant Leaf Diseases:

A functional requirement shows that what the system must do what services the system present to users. It describes a software system or its component. A function is nothing but inputs to the software system, its behavior, and outputs

NON-FUNCTIONAL REQUIREMENTS Implementation of Deep Learning Approach for detection of Plant Leaf Diseases:

• Application is user friendly.
• Application Perform fast manipulation and calculations.
• Application is adaptable.
• Application will be able to work on all types of operating systems.
• Application will be capable to handle multi user activities simultaneously.
• There will be back up system to face any problem in system
• All the options should be learning friendly I.e. member could easily understand what that option will do if he clicked on it.
• Response Time is very awesome.

Some others are:

• Accessibility
• Maintainability
•  Fault Tolerance.
• Security
• Robustnes

Use Case Diagram of Implementation of Deep Learning Approach for detection of Plant Leaf Diseases

a use case diagram can summarize the details of your system’s users   and their interactions with the system. Scenarios in which your system or application interacts with organizations, people, or external systems. Goals that your system or application helps those entities achieve

Usage Scenarios Implementation of Deep Learning Approach for detection of Plant Leaf Diseases:

A brief user story explaining who is using the system and what they are trying to accomplish. A Scenario is made up of a number of simple, discrete steps that are designated as being performed by either the System or a  User.

ADOPTED METHODOLOGY for Implementation of Deep Learning Approach for detection of Plant Leaf Diseases:

The adopted methodology for this project is vu process model. Vu process model is a combination of water-fall model and spiral model. This combination has many advantages. This model has high risk analysis so avoidance of risk would be achieved. This model is easy to understand and use. Now first we will discuss the Water-fall model.

Work Plan of DeepFake Implementation of Deep Learning Approach for detection of Plant Leaf Diseases:

Work plan

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