Kyamelia Roy¹, Sheli Sinha Chaudhuri¹, Sayan Pramanik², Soumen Banerjee^2,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 647-662, 2023, DOI:10.32604/csse.2023.024997

Abstract In recent years, computer vision finds wide applications in maritime surveillance with its sophisticated algorithms and advanced architecture. Automatic ship detection with computer vision techniques provide an efficient means to monitor as well as track ships in water bodies. Waterways being an important medium of transport require continuous monitoring for protection of national security. The remote sensing satellite images of ships in harbours and water bodies are the image data that aid the neural network models to localize ships and to facilitate early identification of possible threats at sea. This paper proposes a deep learning based model capable enough to… More >

Ahmed M. Zeyada^1,*, Khalid A. Al-Gaadi^1,2, ElKamil Tola², Rangaswamy Madugundu², Ahmed A. Alameen²

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1603-1620, 2023, DOI:10.32604/phyton.2023.027267

Abstract The estuary tides affect groundwater dynamics; these areas are susceptible to waterlogging and salinity issues. A study was conducted on two fields with a total area of 60 hectares under a center pivot irrigation system that works with solar energy and belong to a commercial farm located in Northern Sudan. To monitor soil salinity and calcium carbonate in the area and stop future degradation of soil resources, easy, non-intrusive, and practical procedures are required. The objective of this study was to use remote sensing-determined Sentinel-2 satellite imagery using various soil indices to develop prediction models for the estimation of soil… More >