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  • Open Access

    ARTICLE

    Integrating Image Processing Technology and Deep Learning to Identify Crops in UAV Orthoimages

    Ching-Lung Fan1,*, Yu-Jen Chung2

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1925-1945, 2025, DOI:10.32604/cmc.2025.059245 - 17 February 2025

    Abstract This study aims to enhance automated crop detection using high-resolution Unmanned Aerial Vehicle (UAV) imagery by integrating the Visible Atmospherically Resistant Index (VARI) with deep learning models. The primary challenge addressed is the detection of bananas interplanted with betel nuts, a scenario where traditional image processing techniques struggle due to color similarities and canopy overlap. The research explores the effectiveness of three deep learning models—Single Shot MultiBox Detector (SSD), You Only Look Once version 3 (YOLOv3), and Faster Region-Based Convolutional Neural Network (Faster RCNN)—using Red, Green, Blue (RGB) and VARI images for banana detection. Results More >

  • Open Access

    ARTICLE

    Human Face Sketch to RGB Image with Edge Optimization and Generative Adversarial Networks

    Feng Zhang1, Huihuang Zhao1,2,*, Wang Ying1,2, Qingyun Liu1,2, Alex Noel Joseph Raj3, Bin Fu4

    Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1391-1401, 2020, DOI:10.32604/iasc.2020.011750 - 24 December 2020

    Abstract Generating an RGB image from a sketch is a challenging and interesting topic. This paper proposes a method to transform a face sketch into a color image based on generation confrontation network and edge optimization. A neural network model based on Generative Adversarial Networks for transferring sketch to RGB image is designed. The face sketch and its RGB image is taken as the training data set. The human face sketch is transformed into an RGB image by the training method of generative adversarial networks confrontation. Aiming to generate a better result especially in edge, an More >

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