2026-04-17T02:18:42Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/00006633 2021-12-13T05:18:15Z 1582963342780:1605779935331 user-uit

Land Use Classification using Deep Convolutional Neural Network Su Wai Tun Khin Mo Mo Tun One of the challenging issues in high-resolution remote sensing images is classifying land-use scenes with high quality and accuracy Land use classification is required to measure land and its impact on ecosystem. Deep learning is a powerful state-of-the-art technique for image processing including remote sensing images. Land use is classified for environmental monitoring, urban planning and resource management. This proposed system will use in the UC Merced land-use data set. The preprocessing the image can make the improving of image positional accuracy, reducing the storage space, the improving the spectral qualities of image. The pretrained CNN is initially used to learn deep and robust features. Then, the feature extractor of CNN mapps the features and the fully connected layers of CNN are used to obtain excellent results. 2017-11-02 https://meral.edu.mm/records/6633