• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.757-770
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• 2022

Palmprint recognition has drawn increasingly attentions in the past decade due to its uniqueness and reliability. Traditional palmprint recognition methods usually use high-resolution images as the identification basis so that they can achieve relatively high precision. However, high-resolution images mean more computation cost in the recognition process, which usually cannot be guaranteed in mobile computing. Therefore, this paper proposes an improved low-resolution palmprint image recognition method based on residual networks. The main contributions include: 1) We introduce a channel attention mechanism to refactor the extracted feature maps, which can pay more attention to the informative feature maps and suppress the useless ones. 2) The ResStage group structure proposed by us divides the original residual block into three stages, and we stabilize the signal characteristics before each stage by means of BN normalization operation to enhance the feature channel. Comparison experiments are conducted on a public dataset provided by the Hong Kong Polytechnic University. Experimental results show that the proposed method achieve a rank-1 accuracy of 98.17% when tested on low-resolution images with the size of 12dpi, which outperforms all the compared methods obviously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3390-3405
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• 2022

Long Short-Term Memory (LSTM) combined with attention mechanism is extensively used to generate semantic sentences of images in image captioning models. However, features of salient regions and spatial information are not utilized sufficiently in most related works. Meanwhile, the LSTM also suffers from the problem of underutilized information in a single time step. In the paper, two innovative approaches are proposed to solve these problems. First, the Synergy-Gated Attention (SGA) method is proposed, which can process the spatial features and the salient region features of given images simultaneously. SGA establishes a gated mechanism through the global features to guide the interaction of information between these two features. Then, the Recurrent Fusion LSTM (RF-LSTM) mechanism is proposed, which can predict the next hidden vectors in one time step and improve linguistic coherence by fusing future information. Experimental results on the benchmark dataset of MSCOCO show that compared with the state-of-the-art methods, the proposed method can improve the performance of image captioning model, and achieve competitive performance on multiple evaluation indicators.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.124-134
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• 2022

Based on existing research, the psychological state of Chinese students has become a very significant issue that needs to be resolved. In addition to paying attention to the daily life and study of Chinese students, the psychological problems of Chinese students are also worthy of attention. At the same time, if the existing psychological problems are not resolved in time, serious consequences may result. Based on the ART(Attention Restoration Theory) theory, this article uses VR (Virtual Reality) content as a medium, uses 3D modeling software to build a healing scene that helps Chinese students improve their psychological and emotional state, and presents it in a VR device. To achieve the purpose of improving the psychological and emotional state of Chinese students. According to experimental tests, the VR recovery scene constructed by this method can help improve the psychological mood of Chinese international students who already have subliminal depression. The results of independent sample T-tests after data analysis experiments show that after the intervention of the experiment, the depression of the experimental group is significantly improved compared to the control group. It is proved that the method in this study is effective for the mentality and emotion of Chinese international students who have subliminal depression. There is a significant improvement effect.

• ETRI Journal
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• v.36 no.2
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• pp.253-263
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• 2014

In the near future, traditional narrow and fixed viewpoint video services will be replaced by high-quality panorama video services. This paper proposes a visual-attention-aware progressive region of interest (RoI) trick mode streaming service (VA-PRTS) that prioritizes video data to transmit according to the visual attention and transmits prioritized video data progressively. VA-PRTS enables the receiver to speed up the time to display without degrading the perceptual quality. For the proposed VA-PRTS, this paper defines a cutoff visual attention metric algorithm to determine the quality of the encoded video slice based on the capability of visual attention and the progressive streaming method based on the priority of RoI video data. Compared to conventional methods, VA-PRTS increases the bitrate saving by over 57% and decreases the interactive delay by over 66%, while maintaining a level of perceptual video quality. The experiment results show that the proposed VA-PRTS improves the quality of the viewer experience for interactive panoramic video streaming services. The development results show that the VA-PRTS has highly practical real-field feasibility.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.4
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• pp.23-32
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• 2019

Purpose : The purpose of this study was to evaluate the effects of multi-sensory treatment programs on attention and learning in ADHD children. Methods : The program was provided for 50 minutes twice a week for a total of 12 times over 6 weeks. The FAIR concentration test was used to identify the children's concentration of attention before and after the intervention. The children's learning ability was evaluated using K-ABC. Results : When attention was evaluated using FAIR, there was a significant increase in all dependencies of performance value (P), quality value (Q), and continuity value (C) (p>.05). In addition, when learning ability was evaluated using K-ABC, learning ability in general increased significantly (p>.05). The multi-sensory play therapy program had a positive effect on the children's attention and learning ability and thus it is a positive intervention method for children with ADHD. Conclusion : In addition to providing challenging activities, the program showed that it was possible to elicit the children's interest by engaging a variety of senses at the same time. This is believed to have motivated them internally to engage actively in the program.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.749-753
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• 2014

The purpose of this study analyzes the basic elements of film acting based on Stanislavsky Circles of Attention. This research also demonstrates the basic elements on how to become a good film actor. I attempt to interpret Stanislavsky Circles of Attention, in order to adapt the size of camera shots and the location of microphones. This Circles of Attention is an effective method utilized for actors to help them understand and be absorbed in the work of art both in film and stage. It is useful for building a character in realism drama as well as in film. I believe Stanislavsky Circles of Attention is certainly the most advanced acting style in film because it proposes the importance of physical action for actors.

• Korean Institute of Interior Design Journal
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• v.26 no.2
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• pp.3-12
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• 2017

This study has analyzed the features of attention to spacial composition seen in "Seeing ${\leftrightarrow}$ Seen" Correlation of continuous move in the space. The eye-tracking was employed for collecting the data of attention features to the space so that the correlation between visual perception and space could be estimated through the attention features to the difference between spacial composition and display. First, it was confirmed that the attention features varied according to the structure of shops and the exposure degree of selling space, which revealed that, while causing the customers' less attention to both sides of shops, the vanishing-point structure characteristically made their eyes focused on the central part. Second, their initial observation activities were found to be active at the height of their eyes. Third, 10 images were selected as objects for continuous experiment. There was a concern that the central part of each image would be paid intense attention to during the initial observation, but only two of those were found to be so. Fourth, there had been a study result of eye-tracking experiment that the attention had been concentrated on the central part of the image first seen. This study, however, revealed that such phenomenon is limited to the first image. Accordingly, it is necessary to draw up such method for ensuring reliability in order to use the data acquired from any eye-tracking experiment as exclusion of the initial attention time to the first image or of unemployment of the initial image-experiment to analysis.

• Journal of Biomedical Engineering Research
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• v.41 no.5
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• pp.195-202
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• 2020

Needle detection in ultrasound images is sometimes difficult due to obstruction of fat tissues. Accurate needle detection using continuous ultrasound (CUS) images is a vital stage of treatment planning for tissue biopsy and brachytherapy. The main goal of the study is classified into two categories. First, new detection model, i.e. D-Attention Unet, is developed by combining the context information of 3D medical data and CUS images. Second, the D-Attention Unet model was compared with other models to verify its usefulness for needle detection in continuous ultrasound images. The continuous needle images taken with ultrasonic waves were converted into still images for dataset to evaluate the performance of the D-Attention Unet. The dataset was used for training and testing. Based on the results, the proposed D-Attention Unet model showed the better performance than other 3 models (Unet, D-Unet and Attention Unet), with Dice Similarity Coefficient (DSC), Recall and Precision at 71.9%, 70.6% and 73.7%, respectively. In conclusion, the D-Attention Unet model provides accurate needle detection for US-guided biopsy or brachytherapy, facilitating the clinical workflow. Especially, this kind of research is enthusiastically being performed on how to add image processing techniques to learning techniques. Thus, the proposed method is applied in this manner, it will be more effective technique than before.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.476-482
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• 2020

Sequence-to-sequence deep neural networks with attention mechanisms have shown superior performance across various domains, where the sizes of the input and the output sequences may differ. However, if the input sequences are much longer than the output sequences, and the characteristic of the input sequence changes within a single output token, the conventional attention mechanisms are inappropriate, because only a single context vector is used for each output token. In this paper, we propose a double-attention mechanism to handle this problem by using two context vectors that cover the left and the right parts of the input focus separately. The effectiveness of the proposed method is evaluated using speech recognition experiments on the TIMIT corpus.

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1305-1333
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• 2020

Deep learning has recently achieved remarkable results in the field of medical imaging. However, as a deep learning network becomes deeper to improve its performance, it becomes more difficult to interpret the processes within. This can especially be a critical problem in medical fields where diagnostic decisions are directly related to a patient's survival. In order to solve this, explainable artificial intelligence techniques are being widely studied, and an attention mechanism was developed as part of this approach. In this paper, attention techniques are divided into two types: post hoc attention, which aims to analyze a network that has already been trained, and trainable attention, which further improves network performance. Detailed comparisons of each method, examples of applications in medical imaging, and future perspectives will be covered.