Nidhi Gupta
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Assistant Professor
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Nidhi Gupta's research focuses on the application of machine learning and deep learning techniques to address challenges in areas such as surveillance, medical imaging, and automated systems. Her work includes the development of algorithms for real-time weapon detection, utilizing classical machine learning and deep learning methods, with a specific focus on improving performance in low-light conditions.
She has also investigated the use of deep learning for medical image analysis, including the creation of datasets for brain tumor detection and analysis using explainable AI. Her research extends to developing automated systems, such as an electronic meter reading system based on YOLOv5 architecture and a firearm detection system that employs deep learning and super-resolution convolutional neural networks. Additionally, she has explored the application of transfer learning for COVID-19 detection from CT scan images.
Gupta holds an h-index of 13 with over 600 citations across her 78 publications. She has expertise in programming languages including MATLAB and Python, and database management.
Metrics
- h-index: 13
- Publications: 78
- Citations: 607
Selected Publications
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Seeing Through the Mask: AI-Generated Text Detection with Similarity-Guided Graph Reasoning (2025)
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CAMFeND: Credibility-Aware Multimodal Fake News Detection with Rotational Attention (2025)
Collaboration Network
Top Collaborators
- CAMFeND: Credibility-Aware Multimodal Fake News Detection with Rotational Attention
- CAMFeND: Credibility-Aware Multimodal Fake News Detection with Rotational Attention
- Seeing Through the Mask: AI-Generated Text Detection with Similarity-Guided Graph Reasoning
- Seeing Through the Mask: AI-Generated Text Detection with Similarity-Guided Graph Reasoning
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