Dhar, M.K.; Deb, M.; Elangovan, P.; Gopalakrishnan, K.; Sood, D.; Kaur, A.; Parikh, C.; Rapolu, S.; Panjwani, G.A.R.; Ansari, R.A.;
et al. A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Classification. J. Imaging 2025, 11, 243.
https://doi.org/10.3390/jimaging11070243
AMA Style
Dhar MK, Deb M, Elangovan P, Gopalakrishnan K, Sood D, Kaur A, Parikh C, Rapolu S, Panjwani GAR, Ansari RA,
et al. A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Classification. Journal of Imaging. 2025; 11(7):243.
https://doi.org/10.3390/jimaging11070243
Chicago/Turabian Style
Dhar, Mrinal Kanti, Mou Deb, Poonguzhali Elangovan, Keerthy Gopalakrishnan, Divyanshi Sood, Avneet Kaur, Charmy Parikh, Swetha Rapolu, Gianeshwaree Alias Rachna Panjwani, Rabiah Aslam Ansari,
and et al. 2025. "A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Classification" Journal of Imaging 11, no. 7: 243.
https://doi.org/10.3390/jimaging11070243
APA Style
Dhar, M. K., Deb, M., Elangovan, P., Gopalakrishnan, K., Sood, D., Kaur, A., Parikh, C., Rapolu, S., Panjwani, G. A. R., Ansari, R. A., Asadimanesh, N., Karuppiah, S. S., Helgeson, S. A., Akshintala, V. S., & Arunachalam, S. P.
(2025). A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Classification. Journal of Imaging, 11(7), 243.
https://doi.org/10.3390/jimaging11070243
