Field of Internship
Computer Science EngineeringResearch Area of Internship
Deep learningAbout Internship
Assistant Professor from Kumaraguru College of Technology, Coimbatore, is accepting interns interested in the field of Computer Science Engineering, in the research area of Deep learning.
The rise of stress-related disorders and emotional imbalance in modern society has highlighted the urgent need for effective mental health monitoring. Traditional self-reporting methods are often subjective and limited, underscoring the importance of automated approaches. This project explores the use of multimodal deep learning to detect emotions and assess mental well-being by integrating diverse data sources, such as facial expressions, speech signals, and physiological indicators. By leveraging convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the system aims to extract both temporal and spatial features, enabling a comprehensive understanding of an individual’s affective state. Through the combination of multimodal cues, the framework not only improves the robustness and accuracy of emotion recognition but also provides insights into underlying mental health conditions. The outcomes of this project hold promise for early intervention, personalised therapy, and advanced mental health support systems. To support these goals, interns will have opportunities to contribute in the following roles: 1. Project Leader / Coordinator: Managing workflow, coordinating among team members, and ensuring timely progress. 2. Data Collection & Preprocessing Engineer: Gathering multimodal datasets and preparing them through cleaning, labelling, and preprocessing. 3. Model Development Engineer: Designing, implementing, and optimising deep learning models (CNNs, RNNs) for emotion detection. 4. Documentation & Presentation Lead: Preparing technical reports, visualisations, and presentations to effectively communicate findings.
Desired Skills/Techniques
Data Analysis, Jupyter Notebook, JavaScript, Python,Who is eligible?
Bachelors/MastersMode of the Internship
VirtualOpen Positions
The number of interns being selected is flexible and dependent on the quality of applications for this Internship.Internship Duration
6 MonthsPaid/Unpaid
UnPaidApplication opens on
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