Intern Under
Associate Professor

Department of Electronics and Communication Engineering

Sir M. Visvesvaraya Institute of Technology, India

AI-Based Computer Vision System for Environmental Monitoring Internship

Field of Internship

Computer Science Engineering

Research Area of Internship

Deep learning

About Internship

Associate Professor from Sir M. Visvesvaraya Institute of Technology, India, is accepting candidates interested in the field of Computer Science Engineering, in the research area of Deep learning.

The AI-Based Computer Vision System for Environmental Monitoring internship offers an opportunity to work on research and development of deep learning solutions for analyzing environmental data through computer vision techniques. Interns will contribute to the design, implementation, and evaluation of AI models for tasks such as image classification, object detection, segmentation, and environmental pattern analysis. The role involves reviewing and understanding relevant research papers, planning the research methodology, collecting and organizing datasets, preprocessing data, training and testing deep learning models, and evaluating model performance using appropriate metrics. Interns will also compare different model architectures and optimization strategies to identify the most effective approach for the targeted environmental monitoring application. Throughout the internship, participants will gain hands-on experience with deep learning frameworks, computer vision pipelines, dataset preparation, model evaluation, and research-oriented experimentation. The internship also includes preparing technical documentation, project reports, and potentially contributing to a research paper or conference/journal submission based on the outcomes of the work.

Desired Skills/Techniques

Reading and Writing, Critical Reasoning and Aptitude, Qualitative Analysis, Python,

Who is eligible?

Bachelors

Mode of the Internship

Virtual

Open Positions

The number of candidates being selected is flexible and dependent on the quality of applications for this position.

Internship Duration

3 months

Paid/Unpaid

UnPaid

Application opens on

Available round the

Application Deadline

Available round the

Starting date of Internship

Available round the

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