Ms. Kinjal Dave

Principal Researcher-Geoinformatics, SITAICS

PhD (Pursuing), MTech

Email – kinjal.dave@rru.ac.in

About Ms. Kinjal Dave

Kinjal Dave is a Principal Researcher at the Centre for Geoinformatics under SASET. Her research interests lie in the field of remote sensing technology and geographic information systems. She has completed her PhD thesis on Hyperspectral Imaging at Nirma University. Previously, she was involved in a research project sponsored by SAC-ISRO, focusing on the classification of hyperspectral images using deep learning techniques at Nirma University as a Junior Research Fellow. Additionally, she has received a grant from SERB-DST to present her research at the renowned IEEE international conference IGARSS-2023 in Pasadena, California, USA.

Academic Qualification
  • PhD (Thesis submitted), M.Tech (Networking and Communication), B.E. (Electronics and Communication)
  • Experience: Academic (2.5 years) and Research (4 years)
  • Any other relevant Information: She worked as a Junior Research Fellow (JRF) at Nirma University, Ahmedabad, under the SAC-ISRO-sponsored AVIRIS-NG Hyperspectral Airborne Campaign Project titled “Spectral Discrimination and Separability Analysis of Crops and Weeds Using Deep Learning Techniques.” She received a grant from SERB-DST to present her research at the renowned IEEE international conference IGARSS—2023 in Pasadena, California, USA. She has been involved in research projects on remote sensing with SAC-ISRO.
Experience
  • Academic (2.5 years) and Research ( 4 years)
Membership
  • GRSS IEEE Membership
Specialization
  • Hyperspectral Imaging, GIS, Remote sensing image analysis using AI models
Paper Published
  • K. Dave and Y. N. Trivedi, ”Crop-specific hyperspectral band selection method using limited ground-truth data,” in International Journal of Remote Sensing, vol. 60, no. 7, pp. 5375- 5387, Jul. 2022. https://doi.org/10.1007/s12524-022-01545-4 2.
  • K. Dave, T. Vyas, and Y. N. Trivedi, ”Band selection algorithm for crop classification,” Journal of the Indian Society of Remote Sensing, vol. 50, pp. 1487-1498, 2022. https://doi.org/10.1080/01431161.2022.2155085
  • K. Dave, T. Vyas, and Y. N. Trivedi, ”A sample selection method based on similarity measure and fuzziness for crop classification from hyperspectral data,” in International Journal of Remote Sensing, vol. 43, no. 18, pp. 7145-7156, 2022, doi:10.1080/01431161.2022.2022.3112345
  • K. Dave and Y. N. Trivedi, ”A Band Selection Method for Crop Classification Based on Spatial and Spectral Correlation Using Hyperspectral Image,” IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 6081-6084, doi:10.1109/IGARSS52108.2023.10281569
  • K. Dave and Y. N. Trivedi, ”Classification of Crops Based on Band Quality and Redundancy from the Hyperspectral Image,” in ICA 2023-2023 Springer Agriculture-Centric Computation, vol. 1866, Communications in Computer and Information Science, Chandigarh, India, 2023, pp. 154-165, https://doi.org/10.1007/978-3-031-43605-5_12
  • Patel, H., Bhagia, N., Vyas, T., Bhattacharya, B., & Dave, K. (2019, July). Crop identification and discrimination using AVIRIS-NG hyperspectral data based on deep learning techniques. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 3728-3731). IEEE.
  • Shah, Bela, and K. Dave. “SIP based intrusion detection system for VoIP based applications.” Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies. 2016.
Certification
  • Completed Post-Graduate Certificate Course in Geoinformatics from Indira Gandhi National Open University with First-Class in 2019.
  • Completed NPTEL Certification Course in Remote Sensing and Digital Image Processing for Satellite Data with 90% in 2018
Research Projects
  • Worked as Junior Research Fellow (JRF) in Nirma University, Ahmedabad, under SAC-ISRO sponsored AVIRIS-NG Hyperspectral Airborne Campaign Project titled “Spectral Discrimination and Separability Analysis of Crops and Weeds Using Deep Learning Techniques.”
Any other relevant Information
  • Worked as Junior Research Fellow (JRF) in Nirma University, Ahmedabad, under SAC-ISRO sponsored AVIRIS-NG Hyperspectral Airborne Campaign Project titled “Spectral Discrimination and Separability Analysis of Crops and Weeds Using Deep Learning Techniques.” She has received a grant from SERB-DST to present her research at the renowned IEEE international conference IGARSS- 2023 in Pasadena, California, USA