Ranjana Roy Chowdhury, Usma Niyaz, Deepti R. Bathula,” Dual-Level Adaptive Sampling for Enhanced Few-Shot Medical Image Classification” in ISCI 2025 (Best Paper Award)
Ranjana Roy Chowdhury,Deepti R. Bathula,” Class-Wise Feature Map Selection Based Prototypical Networks” accepted in ISBI 2024 (Short Paper)
Ranjana Roy Chowdhury,Deepti R. Bathula,”Influencial Prototypical Networks for Few Shot Learning: A Dermatological Case Study” accepted in ISBI 2022.
Link: https://ieeexplore.ieee.org/document/9761403
Ranjana Roy Chowdhury, Deepti R. Bathula, “Selective Feature Representation in Prototypical
Networks for Medical Image Classification” (Under Review in International Journal of Computer Applications(2025)).
Ranjana Roy Chowdhury, Usma Niyaz, Deepti R. Bathula, “Prototypical Aggregate Network - Boosting Few-Shot Learning for Medical Image Classification” (Under Major Review in Multimedia Tools and Applications (2024)).
Soumi Chattopadhyay, Chandranath Adak, Ranjana Roy Chowdhury,” FES: A Fast Efficient Scalable QoS Prediction Framework”, (Submitted to IEEE Transactions on Services Computing (2021)).
Link: https://arxiv.org/abs/2103.07494
Ranjana Roy, Shivam Gupta, Sravanthi Chede,” World War III Analysis using Signed Social Networks”, in
Social Network Analysis and Mining (2021).
Ranjana Roy Chowdhury, Soumi Chattopadhyay, Chandranath Adak,"CAHPHF: Context-Aware Hierarchical QoS Prediction with Hybrid Filtering", in IEEE Transactions on Services Computing (2020).
Link: https://ieeexplore.ieee.org/document/9275357
Ilyas Abbasi, Ranjana Roy Chowdhury, H. Leishang Chanu, Sujit Rabha, Dr. Tapadhir Acharjee, "A Hybrid Image Steganography Method", in International Journal of Research Technology and Engineering (IJRTE), ISSN:2277- 3878, Volume-8 Issue-3, September 2019.
Link: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.ijrte.org/wp-content/uploads/papers/v8i3/C6436098319.pdf
C. Adak, D. Ghosh, R. R. Chowdhury, S. Chattopadhyay, “COVID-19-affected Medical Image Analysis using Denser Net”, in Book Chapter of Data Science for COVID-19, Eds. U. Kose, D. Gupta, V.H.C. de Albuquerque, A. Khanna, Elsevier, 2020.
Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137508/