Dr. Joohi Chauhan

Assistant Professor
Department of Computer Science & Engineering
Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India-211004
E-mail: joohi[at]mnnit[dot]ac[dot]in
Telephone: +91 8920420559(O)

Research Publications

Patents:

“Secure Authentication using dynamic passcodes”, Patent No. 430469, 2646/DEL/2014, Government of India – The patent Office, April 28, 2023. Filed in Canada also (Application no. 2904646)

Book Chapter:

K. Agrawal, J. Chauhan, Vamseedharan, and P. Goyal, “Information Technology in Burn Care,” in Textbook of Plastic, Reconstructive, and Aesthetic Surgery, Thieme, vol. 5, pp. 697-714, 2020.

Journals:

Z. Lai, J. Chauhan, D. Chen, B. N. Dugger, S-C Cheung, and C-N Chuah, "Semi-Path: An interactive semi-supervised learning framework for gigapixel pathology image analysis," Smart Health, 32: 100474, 2024. (Accepted/Presented in CHASE Conference)

A. Villablanca, B. N. Dugger, S. Nuthikattu, J. Chauhan, S. Cheung, C-N. Chuah, S. L. Garrison, D. Milenkovic, J. E. Norman, L. C. Oliveira, B. P. Smith, S. D. Brown "How cy pres promotes transdisciplinary convergence science: an academic health center for women’s cardiovascular and brain health," Journal of Clinical and Translational Science, 8, 2024.

J. Chauhan and J. Bedi, “EffViT-COVID - A Dual-path Network for COVID-19 Percentage Estimation,” Expert Systems with Applications, 213-PartB, 2023. (H-Index: 249)

M. Singh, J. Chauhan, M. Suhaib, S. Verma, and P. Goyal, “IPCRF: An End-to-end Indian Paper Currency Recognition Framework for Blind and Visually Impaired People,” IEEE Access,10, 2022. (H-Index: 204)

J. Chauhan and P. Goyal, “Convolution Neural Network for Effective Burn Region Segmentation of Color Images,” Burns, 47(4): 854-862, 2021. (H-Index: 113)

J. Chauhan and P. Goyal, “BPBSAM: Body Part specific Burn Severity Assessment Model using Deep Convolutional Neural Network,” Burns, 46(6):1407-23, 2020. (H-Index: 113)

Conference Proceedings:

Z. Lai, J. Chauhan, B. N. Dugger, C-N. Chuah, "Bridging the Pathology Domain Gap: Efficiently Adapting CLIP for Pathology Image Analysis with Limited Labeled Data," European Conference on Computer Vision, Oct 2024. (Core A*, H5-index: 238) Acceptance rate 27.9%

J. Chauhan, P. L. Rosin, P. Goyal, "BuRnSNet: BURN REGION SEGMENTATION NETWORK FROM COLOR IMAGES WITH TWO-WAY CNN," IEEE International Conference on Image Processing, Sep. 2024 (Qualis A, Core B)

A. Patel, A. Maurya, Alaukik, J. Chauhan, "PG-YOLO: Programmable Gradient YOLO and Benchmark for Prohibited Item Detection in X-ray Security Inspection" CVIP, Dec. 2024

Z. Lai, LC Oliveira, J. Chauhan, BN. Dugger, C-N. Chuah, “CLIPath: Fine-tune CLIP with Visual Feature Fusion for Pathology Image Analysis Towards Minimizing Data Collection Efforts,” Workshop on Computer Vision for Automated Medical Diagnosis at International Conference on Computer Vision (ICCV), Paris, Oct. 02-06, 2023. (core A*)

J. Chauhan and P. Goyal, “A Multi-path CNN for Automated Skin Lesion Segmentation,” International Joint Conference on Neural Network (IJCNN), China, July 2021.

J. Chauhan and P. Goyal, “Deep Learning based fully automatic efficient Burn Severity Estimators for better Burn Diagnosis,” International Joint Conference on Neural Network (IJCNN), Glasgow, UK, July 2020. (core A)

J. Chauhan, R. Goswami, and P. Goyal, “Using Deep Learning to Classify Burnt Body Part Images for Better Burn Diagnosis,” In proc. Processing and Analysis of Biomedical Information, SaMBa MICCAI, Granada, Spain, Sep 2018. (core A)