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ORCIDSuchismita Das
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2020 – today
- 2024
[j8]Suchismita Das, Rajni Dubey, Biswajit Jena, Lung-Wen Tsai, Sanjay Saxena
:
WU-Net++: A novel enhanced Weighted U-Net++ model for brain tumor detection and segmentation from multi-parametric magnetic resonance scans. Multim. Tools Appl. 83(28): 71885-71908 (2024)- [i4]Tanujit Chakraborty, Shraddha M. Naik, Swarup Chattopadhyay, Suchismita Das:
Learning Patterns from Biological Networks: A Compounded Burr Probability Model. CoRR abs/2407.04465 (2024) - 2023
- [c6]Shrejal Singh, Minakhi Rout, Rohan Lana, Suchismita Das, Junali Jasmine Jena, Anuja Kumar Acharya:
Machine Learning Approaches for Improving the Survival Prediction Rate in Heart Failure Patients. OCIT 2023: 508-513 - [c5]Suchismita Das, Subhankar Samanta, Minakhi Rout:
Analysis of Pneumonia detection in X-ray images using different filters based Convolution Neural Networks. OCIT 2023: 787-792 - [i3]Suchismita Das, Nikhil R. Pal:
Feature selection simultaneously preserving both class and cluster structures. CoRR abs/2307.03902 (2023) - 2022
- [j7]Tanujit Chakraborty, Swarup Chattopadhyay, Suchismita Das, Uttam Kumar, J. Senthilnath:
Searching for Heavy-Tailed Probability Distributions for Modeling Real-World Complex Networks. IEEE Access 10: 115092-115107 (2022) - [j6]Suchismita Das, Gopal Krishna Nayak, Luca Saba, Mannudeep K. Kalra, Jasjit S. Suri, Sanjay Saxena:
An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review. Comput. Biol. Medicine 143: 105273 (2022) - [j5]Suchismita Das, Srijib Bose, Gopal Krishna Nayak, Sanjay Saxena:
Deep learning-based ensemble model for brain tumor segmentation using multi-parametric MR scans. Open Comput. Sci. 12(1): 211-226 (2022) - [j4]Suchismita Das, Srijib Bose, Gopal Krishna Nayak, Suresh Chandra Satapathy, Sanjay Saxena:
Brain tumor segmentation and overall survival period prediction in glioblastoma multiforme using radiomic features. Concurr. Comput. Pract. Exp. 34(20) (2022) - [j3]Suchismita Das, Nikhil R. Pal:
Supervised learning of explicit maps with ability to correct distortions in the target output for manifold learning. Inf. Sci. 614: 311-324 (2022) - [j2]Souma Kanti Paul, Sadia Riaz, Suchismita Das:
Adoption of Artificial Intelligence in Supply Chain Risk Management: An Indian Perspective. J. Glob. Inf. Manag. 30(8): 1-18 (2022) - [j1]Suchismita Das, Nikhil R. Pal:
Nonlinear Dimensionality Reduction for Data Visualization: An Unsupervised Fuzzy Rule-Based Approach. IEEE Trans. Fuzzy Syst. 30(7): 2157-2169 (2022) - [c4]Suchismita Das, Nikhil R. Pal:
Understanding the Classes Better with Class-Specific and Rule-Specific Feature Selection, and Redundancy Control in a Fuzzy Rule Based Framework. IDEAL 2022: 338-347 - [i2]Suchismita Das, Nikhil R. Pal:
Understanding the classes better with class-specific and rule-specific feature selection, and redundancy control in a fuzzy rule based framework. CoRR abs/2208.01294 (2022) - 2021
- [c3]Rahul Jain, Anoushka Sutradhar, Amiya K. Dash, Suchismita Das:
Automatic Multi-organ Segmentation on Abdominal CT scans using Deep U-Net Model. OCIT 2021: 48-53 - 2020
- [c2]Souma Kanti Paul, Sadia Riaz, Suchismita Das:
Organizational Adoption of Artificial Intelligence in Supply Chain Risk Management. TDIT (1) 2020: 10-15 - [i1]Suchismita Das, Nikhil R. Pal:
Nonlinear Dimensionality Reduction for Data Visualization: An Unsupervised Fuzzy Rule-based Approach. CoRR abs/2004.03922 (2020)
2010 – 2019
- 2019
- [c1]Suchismita Das, Nikhil R. Pal:
An Unsupervised Fuzzy Rule-Based Method for Structure Preserving Dimensionality Reduction with Prediction Ability. AIAI 2019: 413-424
Coauthor Index
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