• ETRI Journal
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• v.46 no.2
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• pp.290-306
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• 2024

To treat the novel COronaVIrus Disease (COVID), comparatively fewer medicines have been approved. Due to the global pandemic status of COVID, several medicines are being developed to treat patients. The modern COVID medicines development process has various challenges, including predicting and detecting hazardous COVID medicine responses. Moreover, correctly predicting harmful COVID medicine reactions is essential for health safety. Significant developments in computational models in medicine development can make it possible to identify adverse COVID medicine reactions. Since the beginning of the COVID pandemic, there has been significant demand for developing COVID medicines. Therefore, this paper presents the transferlearning methodology and a multilabel convolutional neural network for COVID (MLCNN-COV) medicines development model to identify negative responses of COVID medicines. For analysis, a framework is proposed with five multilabel transfer-learning models, namely, MobileNetv2, ResNet50, VGG19, DenseNet201, and Inceptionv3, and an MLCNN-COV model is designed with an image augmentation (IA) technique and validated through experiments on the image of three-dimensional chemical conformer of 17 number of COVID medicines. The RGB color channel is utilized to represent the feature of the image, and image features are extracted by employing the Convolution2D and MaxPooling2D layer. The findings of the current MLCNN-COV are promising, and it can identify individual adverse reactions of medicines, with the accuracy ranging from 88.24% to 100%, which outperformed the transfer-learning model's performance. It shows that three-dimensional conformers adequately identify negative COVID medicine responses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5963-5980
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• 2017

Image scrambling is an important technology in information hiding, where the Arnold transformation is widely used. Several researchers have proposed the application of $H{\acute{e}}non$ map in square image scrambling, and certain improved technologies require scrambling many times to achieve a good effect without resisting chosen-plaintext attack although it can be directly applied to non-square images. This paper presents a non-square image scrambling algorithm, which can resist chosen-plaintext attack based on a chaotic two-dimensional Sine Logistic modulation map and $H{\acute{e}}non$ map (2D-SLHM). Theoretical analysis and experimental results show that the proposed algorithm has advantages in terms of key space, efficiency, scrambling degree, ability of anti-attack and robustness to noise interference.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.621-624
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• 1999

This paper describes a distance estimation method of object's motion in soccer image sequence by tracking field features. And we quantitatively evaluate the estimation accuracy We suppose that the input image sequence is taken with a camera on static axis and includes only zooming and panning transformation between frames. Adaptive template matching is adopted for non-rigid object tracking. For background compensation, feature templates selected from reference frame image are matched in following frames and the matched feature point pairs are used in computing Affine motion parameters. A perspective displacement field model is used for estimating the real distance between two position on Input Image. To quantitatively evaluate the accuracy of the estimation, we synthesized a 3 dimensional virtual stadium with graphic tools and experimented on the synthesized 2 dimensional image sequences. The experiment shows that the average of the error between the actual moving distance and the estimated distance is 1.84%.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.348-351
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• 2004

In this paper, we propose the face recognition method using Harr wavelet transform and 2D PCA. While previous PCA computed the covariance matrix by using one dimensional vectors, 2D PCA computed the covarinace matrix by using direct two dimensional image and extracted feature vector by solving eigenvalue problem. To gain the face image having the low dimension and robust property, the proposed method uses wavelet transformation. We apply the LL band image data to 2D PCA for face recognition. The experimental results indicate that our method improves recognition rate than 2D PCA into original image.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.125-137
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• 2004

In case of using image sequence taken from a moving camera along a road in an urban area, general video mosaicing technique based on a single baseline cannot create 2-D image mosaics. To solve the drawback, this paper proposed a new image mosaicing technique through 3-D multi-baselines that can create image mosaics in 3-D space. The core of the proposed method is that each image frame has a dependent baseline, an equation of first order, calculated by using ground control point (GCP) of optical flows. The proposed algorithm consists of 4 steps: calculation of optical flows using hierarchical strategy, calculation of camera exterior orientation, determination of multi-baselines, and seamless image mosaics. This paper realized and showed the proposed algorithm that can create efficient image mosaics in 3-D space from real image sequence.

• Journal of Korea Game Society
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• v.10 no.1
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• pp.135-146
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• 2010

The development of image technologies in such area as broadcasting and movies has recently increased our attention to 3D stereoscopic images. In addition, the development of stereoscopic image representation technologies in 3D contents becomes more active over time due to the representational limitations of 2D images. Without limitation to the above-mentioned area, stereoscopic image technologies have been developed and studied so that they can be widely accessed in diverse areas including medical services and education. Due to the refined production, however, required to represent a three dimensional effects and the fatigue caused by the perception of a three dimensional effects, the stereoscopic image technologies are not combined into real time systems such as games where environments change unforeseeably. In this study we design a technique to adjust the depth scaling that will enable efficient management of a three dimensional effects and to relieve fatigue through automatic view point interval adjustment in accordance with situations based on the geometrical structure of the DirectX SDK graphic pipeline. Through this, we would like to suggest a new alternative idea to activate the production of games combined with stereoscopic image technologies.

• Proceedings of the Optical Society of Korea Conference
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• 2003.02a
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• pp.290-291
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• 2003

Optical Coherence Tomography is a new medical dianostic imaging technology which can perform micron resolution cross-sectional or tomograpic imaging in biological tissue. In this paper, we analyze OCT system. And we have 2-dimensional OCT image implementation using low coherence SLD.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.164-165
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• 1979

Two dimensional kernels which reconstruct the tomographic image from the blurred one formed by simple back-projection are investigated and their performances are compared. These kernels are derived from tile point spread function of the tomographic system and have the form of a ramp filter modified by several window functions to suppress ringing in the reconstruction. Computer simulation using a computer generated phantom image data with different correction functions(kernels) has been carried out. In this simulation, filtering in frequency domain by 2-D FFT technique or in space domain by 2-D direct convolution is considered. It is found that the-computation time required for real space convolution technique is much larger than that of Fourier 2-D filtering technique in the pratical situation.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.1017-1019
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• 1999

In this paper we present 2-dimensional image recovery method using Hadamard transform. Generally, the methods of Hadamard transform are more useful tools and much simplier than those of Fourier transform. The Hadamard transform can improve estimates when the detector is the source of noise. We take into account nonidealities in the system for the further improved image We also present the average mean square error(AMSE) associated with estimates with the results from computer simulations.

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.4
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• pp.28-37
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• 1993

Flow characteristics within the three-dimensional square cavity are studied experimentally by adopting PIV(Particle Image Velocimetry). A new method for tracking the same particle pairs in the consecutive flow image is suggested resulting in more effective acquisition of the velocity vectors. Two methods for supplying the shearing stress within the cavity are developed by continuous moving belt and 2-dimensional plane Poiseuille flow. The effect of TGL vortex in the case of belt-moving flow is remarkable owing to the distribution of the kinetic energy in the spanwise direction. But, for the plane Poiseuille flow, velocity profiles similar to a forced vortex are obtained and its tendency increases with the Reynolds number.