• Smart Media Journal
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• v.12 no.1
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• pp.24-31
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• 2023

Meta-learning is metacognition that instantly distinguishes between knowing and unknown. It is a learning method that adapts and solves new problems by self-learning with a small amount of data.A few-shot learning method is a type of meta-learning method that accurately predicts query data even with a very small support set. In this study, we propose a method to solve the limitations of the prototype created with the mean-point vector of each class. For this purpose, we use the few-shot learning method that created the prototype used in the few-shot learning method as the median prototype. For quantitative evaluation, a handwriting recognition dataset and mini-Imagenet dataset were used and compared with the existing method. Through the experimental results, it was confirmed that the performance was improved compared to the existing method.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.30 no.2
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• pp.1-13
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• 2012

This study aimed at learning the values and meanings of the letters carved on the rocks all over Mt. Sangdu located at the boundary between Kimje-si and Jeongeup-si of Jeollabuk-do by grasping the current state of them, investigating the patterns and contents of them, and understanding the spatial and landscape properties of the region where the rocks are scattered. The results of this study are as follows; The name of Mt. Sangdu came from the mountain with the same name located in India where Buddha were seeking the truth, and means auspicious. With the recognition of ancient maps and books, various propitious spots also made the landscape symbols of Mt. Sangdu solidify. Whoam, Chaangsuk-Kim, Weolgye Young-Cho Song and the members of Cheonggye Society like Dongcho Seok-Gon Kim led the creation of the rocks, and the 41 letter-carved rocks all over four water systems were found out and all of them were carved with Chinese characters. The letters were usually carved on flat and broad rocks, and they mainly had the shape of a small waterfall and a wide waterfall of under 1 meter height. 25(60.9%) of the carved letters were about moral training, and it seemed that they wanted to protect their pride under the shackle of the Japanese colonization over Korea. The styles of handwriting are Hangseo and Jeonseo except for names, and show various and complex styles. The mix composition of the carved letters of 'Yusubulbu(流水不腐)' of Choseo and the rocks of Takjok(濯足) is extraordinary, and the letters carved as the shape of Nakkwan(落款) have artistic value and degree of finishing. It seemed that intellectuals during the Japanese colonization over Korea in the 1930s considered Mt. Sangduasa highly valuable region because they expressed their hope and wish for the new world on the rocks. The letters on the rocks of Mt. Sangdu are invaluable cultural landscaping elements for the improvement of landscaping symbolism of Mt. Sangdu because of colliding values and spirits of the time of 'the anguish and pain of intellectuals' and 'the status of living joyfully outside of the mundane world.'