Dhamodharan R

• Content-based image retrieval. In that, I'm working on image quality enhancement and removal of annotations from the 2D drawings to improve the accuracy of similarity search.
• Fast retrieval of images using indexing(Vector database).
• Annotation-based image classification helps the customer to visualize the count of the template type.

AI Model to Predict Plant Disease

1. Introduction

• The problem of plant diseases poses a significant threat to crop production and food security worldwide.
• Early detection and accurate diagnosis of plant diseases are crucial for effective disease management.
• Artificial Intelligence (AI) models can be developed to predict and diagnose plant diseases, aiding farmers in taking timely and appropriate actions.
• Data Collection
• A large dataset of images of healthy and diseased plants is required for training the model and it was directly collected from the field.

Impact:

• Early detection: An AI model can accurately detect plant diseases at an early stage, allowing for timely intervention and preventing the spread of diseases to other plants.
• Increased crop yield: By identifying diseases early, farmers can take appropriate measures to control and manage the spread, leading to higher crop yields and reduced losses.
• Reduced pesticide usage: Accurate prediction of plant diseases can help farmers optimize the use of pesticides, reducing the overall quantity required and minimizing environmental impact.

1. Visualize productivity data: Use data visualization techniques to present productivity data in an easy-to-understand format. This can include creating charts, graphs, and dashboards that highlight key metrics and trends.

2. Analyze productivity trends: Analyze the productivity data to identify patterns, trends, and insights. This can involve performing statistical analysis, trend analysis, and correlation analysis to gain a deeper understanding of the factors that impact productivity.

Impact:

• Visualize company's productivity
• Gain knowledge from data
• Boost business growth

• International conference website for college
• Purpose: To provide information about an international conference organized by a college and make the registration process easy for users.
• Features:

1. Event Information: The website should display details about the conference, such as the theme, date, location, and schedule.

2. Registration: Users should be able to register for the conference through the website. The registration process should be user-friendly and include options for different types of participants

Impact:

• Provides a platform for colleges to host international conferences and showcase their research and academic work to a global audience.
• Facilitates the dissemination of knowledge and promotes collaboration among researchers, scholars, and students from different countries.
• Allows participants to access essential information about the conference, such as the schedule, keynote speakers, session topics, and paper submission guidelines.
• Simplifies the registration process by offering an online registration system, eliminating the need for manual paperwork and reducing administrative burden.

Machine learning to recognize the face

1. Data collection: Gather a large dataset of images containing faces. This dataset should include a diverse range of individuals with varying facial features and expressions.

2. Preprocessing: Preprocess the collected images to standardize them. This may include resizing the images, converting them to grayscale, and normalizing the pixel values.

Impact:

• Enhanced security and surveillance systems
• Efficient and convenient authentication methods

Work List:

1. Collecting COVID-19 data on a daily basis from reliable sources such as government health departments, World Health Organization (WHO), and other trusted sources.

2. Ensuring the collected data is accurate and up-to-date by cross-referencing multiple sources and verifying the information.

3. Organizing the collected data in a structured format, such as a spreadsheet or database, to facilitate further analysis and visualization.

4. Cleaning and preprocessing the data to remove any inconsistencies,

Impact of data collection and data visualization in displaying COVID-19 cases on a daily basis:

• Improved awareness and understanding: Data collection and visualization help in providing accurate and up-to-date information about the number of COVID-19 cases, allowing individuals and communities to stay informed and make informed decisions regarding their health and safety.
• Identification of trends and patterns: By collecting and analyzing data on a daily basis, data visualization can help identify trends and patterns in the spread of COVID-19.