• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.653-663
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• 2012

Using soft classification, it is possible to obtain the land cover proportions from the remotely sensed image. These land cover proportions are then used as input data for a procedure called "super-resolution mapping" to produce the predicted hard land cover layers at higher resolution than the original remotely sensed image. Superresolution mapping can be implemented using a number of algorithms in which the Hopfield Neural Network (HNN) has showed some advantages. The HNN has improved the land cover classification through superresolution mapping greatly with the high resolution data. However, the super-resolution mapping is based on the spatial dependence assumption, therefore it is predicted that the accuracy of resulted land cover classes depends on the relative size of spatial features and the spatial resolution of the remotely sensed image. This research is to evaluate the capability of HNN to implement the super-resolution mapping for SPOT image to create higher resolution land cover classes with different zoom factor.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.3
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• pp.272-281
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• 2013

Traffic Collision Avoidance System (TCAS) is designed to enhance safety in aircraft operations, by reducing the incidences of mid-air collision between aircraft. The current version of TCAS provides only vertical resolution advisory to the pilots, if an aircraft's collision with another is predicted to be imminent, while efforts to include horizontal resolution advisory have been made, as well. This paper introduces a collision resolution algorithm, which includes both vertical and horizontal avoidance maneuvers of aircraft. Also, the paper compares between the performance of the proposed algorithm and that of algorithms with only vertical or horizontal avoidance maneuver of aircraft.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.91-96
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• 1995

In this paper we propose algorithms for high resolution image sequence interpolation. Image sequences, in general, are assumed to have greater amount of information than a still image. By this reason, image sequences can be used to improve the resolution of interpolated image sequences. Therefore the proposed algorithms can be the theoretical basis for interpolating dynamic image sequences. In order to demonstrate the validity of the proposed algorithms, experimental results using both synthetic and real test images are presented.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.266-269
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• 2007

This paper reports the preliminary results on the study of radargrammetry especially for a high-resolution satellite synthetic aperture radar system. Theoretical configurations for radargrammetry in terms of coverage, orbit selection, incidence angles, height sensitivity of parallax and height resolution of DEM were calculated according to the proposed orbit characteristics and the imaging modes of KOMPSAT-5 SAR. Possible imaging strategies and mission scenarios for coverage versus rapidity are suggested for a future mission dedicated to radargrammetry.

• Bulletin of the Korean Chemical Society
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• v.25 no.10
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• pp.1471-1473
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• 2004

An efficient dynamic kinetic resolution of racemic ${\beta}$-hydroxyalkylferrocene and 1,1'-bis( ${\beta}$-hydroxyalkyl)-ferrocene derivatives was achieved using lipase/ruthenium-catalyzed transesterification in the presence of an acyl donor. The racemic ${\beta}$-hydroxyalkylferrocene derivatives were successfully transformed to the corresponding chiral acetates of high optical purities in high yields.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.3-11
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• 2006

The need for edge detection about topography data from the high resolution satellite imagery is happening with increasing frequency according to many people utilize the its imagery as various fields recently. Many experts is recognizing of other GIS will make use of the road detection from the high resolution satellite imagery, including ITS (Intelligent Transportation Systems) and urban planning. This paper is comparative analysis of LPF (Low Pass Filtering) and HPF (High Pass Filtering) for roads edge detection from high resolution satellite imagery. As a result, LPF and HPF can be highlight selective pixels at edge area about input data. In case or applying to other techniques such as LPF for the same purpose, they aye more effective for wide road width which often cause the slight distortion of boundary or overall change of brightness values on the whole Image. Whereas, HPF has ability to enhance selectively detailed components in a target image.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.141-155
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• 2021

Purpose: To develop a 3D magnetic resonance fingerprinting (MRF) method for application in high resolution knee cartilage PD, T₁, T₂ mapping. Materials and Methods: A novel 3D acquisition trajectory with golden-angle rotating radial in k_xy direction and interleaved echo planar imaging (EPI) acquisition in the k_z direction was implemented in the MRF framework. A centric order was applied to the interleaved EPI acquisition to reduce Nyquist ghosting artifact due to field inhomogeneity. For the reconstruction, singular value decomposition (SVD) compression method was used to accelerate reconstruction time and conjugate gradient sensitivity-encoding (CG-SENSE) was performed to overcome low SNR of the high resolution data. Phantom experiments were performed to verify the proposed method. In vivo experiments were performed on 6 healthy volunteers and 2 early osteoarthritis (OA) patients. Results: In the phantom experiments, the T₁ and T₂ values of the proposed method were in good agreement with the spin-echo references. The results from the in vivo scans showed high quality proton density (PD), T₁, T₂ map with EPI echo train length (N_ETL = 4), acceleration factor in through plane (R_z = 5), and number of radial spokes (N_spk = 4). In patients, high T₂ values (50-60 ms) were seen in all transverse, sagittal, and coronal views and the damaged cartilage regions were in agreement with the hyper-intensity regions shown on conventional turbo spin-echo (TSE) images. Conclusion: The proposed 3D MRF method can acquire high resolution (0.5 mm³) quantitative maps in practical scan time (~ 7 min and 10 sec) with full coverage of the knee (FOV: 160 × 160 × 120 mm³).

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.438-445
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• 2017

This paper presents a low-power high-resolution band-pass ${\Sigma}{\Delta}$ ADC for accelerometer applications. The proposed band-pass ${\Sigma}{\Delta}$ ADC consists of a high-performance 6-th order feed-forward ${\Sigma}{\Delta}$ modulator with 1-bit quantization and a low-power, area-efficient digital filter. The ADC is fabricated in 180 nm 1P6M mixed-signal CMOS process with a die area of $5mm^2$. This high-resolution ADC got 90 dB peak signal to noise plus distortion ratio (SNDR) and 96 dB dynamic range (DR) over 4 kHz bandwidth, while the intermediate frequency (IF) is shifting from 100 KHz to 200 KHz. The power dissipation of the chip is 5.6 mW under 1.8 V (digital)/3.3 V (analog) power supply.

• Bulletin of the Korean Chemical Society
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• v.32 no.7
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• pp.2345-2350
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• 2011

Variable temperature high-resolution $^{19}F$ magic angle spinning (MAS) solid-state NMR spectroscopy was used to characterize fluorocarbon (FKM) rubbers. The high-resolution spectra of copolymers made from two monomers, vinylidene fluoride and hexafluoropropene, and terpolymers composed of vinylidene fluoride, hexafluoropropene, and tetrafluoroethylene, were obtained using MAS speeds of up to 18 kHz combined with high temperatures of up to 200 $^{\circ}C$ at a magnetic field strength of 9.4 Tesla. From these high resolution solid-state NMR spectra, we were able to assign the spectral peaks and differentiate the copolymer FKM from the terpolymer FKM. We also determined quantitatively the monomer compositions of each FKM rubber.