• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.21-26
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• 2016

This paper presents a step-down DC-DC buck converter with a CCM/DCM dual-mode function for the internal power stage of portable electronic device. The proposed converter that is operated with a high frequency of 1 MHz consists of a power stage and a control block. The power stage has a power MOS transistor, inductor, capacitor, and feedback resistors for the control loop. The control part has a pulse width modulation (PWM) block, error amplifier, ramp generator, and oscillator. In this paper, an external capacitor for compensation has been replaced with a multiplier equivalent CMOS circuit for area reduction of integrated circuits. In addition, the circuit includes protection block, such as over voltage protection (OVP), under voltage lock out (UVLO), and thermal shutdown (TSD) block. The proposed circuit was designed and verified using a $0.18{\mu}m$ CMOS process parameter by Cadence Spectra circuit design program. The SPICE simulation results showed a peak efficiency of 94.8 %, a ripple voltage of 3.29 mV ripple, and a 1.8 V output voltage with supply voltages ranging from 2.7 to 3.3 V.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.