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Shounak Chakraborty 0002
Person information
- affiliation: Indian Institute of Information Technology Guwahati, Department of Computer Science and Engineering, Assam, India
- not to be confused with: Shounak Chakraborty 0001
Other persons with the same name
- Shounak Chakraborty 0001
— Norwegian University of Science and Technology (NTNU), Trondheim, Norway (and 1 more)
- Shounak Chakraborty 0003 — Max Planck Institute for Informatics, Saarbrücken, Germany
- Shounak Chakraborty 0004 — Indian Institute of Information Technology Design and Manufacturing, Kurnool, India
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2020 – today
- 2024
- [j4]Indrajit Kalita, Shounak Chakraborty, Talla Giridhara Ganesh Reddy, Moumita Roy:
A deep learning-based technique for firm classification and domain adaptation in land cover classification using time-series aerial images. Earth Sci. Informatics 17(1): 655-678 (2024) - 2020
- [j3]Shounak Chakraborty
Handling the Class Imbalance in Land-Cover Classification Using Bagging-Based Semisupervised Neural Approach. IEEE Geosci. Remote. Sens. Lett. 17(9): 1493-1497 (2020)
2010 – 2019
- 2019
- [j2]Shounak Chakraborty
Semisupervised Two-Level Fusion-Based Autoencoded Approach for Low-Cost Domain Adaptation of Remotely Sensed Images. IEEE Geosci. Remote. Sens. Lett. 16(7): 1041-1045 (2019) - [c4]Indrajit Kalita
Deep Ensemble Network for Handling Class-Imbalance Problem in Land-Cover Classification. ICIT 2019: 505-509 - [c3]Shounak Chakraborty, Indrajit Kalita
An Adversarial Learning Mechanism for Dealing with the Class-Imbalance Problem in Land-Cover Classification. HIS 2019: 188-196 - [c2]Shounak Chakraborty
Unsupervised domain adaptation in land-cover classification under neural approach using feature-level ensemble. IGARSS 2019: 724-727 - 2018
- [j1]Shounak Chakraborty
A neural approach under transfer learning for domain adaptation in land-cover classification using two-level cluster mapping. Appl. Soft Comput. 64: 508-525 (2018) - 2016
- [c1]Shounak Chakraborty
Domain adaptation for land-cover classification of remotely sensed images using ensemble of Multilayer Perceptrons. RAIT 2016: 523-528
Coauthor Index
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