• M. Rega
• Dr. S. Sivakumar

Presently, remote sensing images (RSIs) are frequently used in the description of urban and rural regions, change detection, and other fields. In general, the RSI is high-resolution and covers extensive and diverse data, appropriate analysis of RSIs is most significant. Scene classification using deep learning (DL) is a common and effective way in RS and geospatial analysis. It is most vital in environmental monitoring, mapping, land planning, and land management. Nevertheless, the current techniques are issues as vulnerability to noise interference, lower classification accuracy, and poor generalization skills. DL models like Convolutional Neural Networks (CNNs) are exposed significant result in image detection tasks, making them suitable for scene classification in RSIs. So, this study develops a new Water Flow Optimizer with Deep Learning Enabled Scene Detection and Classification (WFODL-SDC) approach on RSIs. The main focus of the WFODL-SDC approach is in the optimal detection and classification of various scenes that exist in it. To accomplish this, the WFODL-SDC technique involves an adaptive median filtering (AMF) method for removing the noise that exists in it. Besides, the WFODL-SDC technique uses SE-DenseNet method for the derivation of useful feature vectors. For hyperparameter tuning of the SE-DenseNet method, the WFO methodology is employed. At last, autoencoder (AE) has been executed for the recognition and classification of various kinds of scenes. The simulation result analysis of the WFODL-SDC technique undergoes utilizing benchmark image database. The experimental values inferred that the WFODL-SDC methodology obtains optimal results with other recent approaches.

"Water Flow Optimizer with Deep Learning Enabled Scene Detection and Classification Model on Remote Sensing Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.a67-a88, November-2024, Available :http://www.jetir.org/papers/JETIR2411007.pdf

"Water Flow Optimizer with Deep Learning Enabled Scene Detection and Classification Model on Remote Sensing Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppa67-a88, November-2024, Available at : http://www.jetir.org/papers/JETIR2411007.pdf