• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.489-489
• /
• 2000

Recently, Reinforcement Learning(RL) methods have been used far teaming problems in Partially Observable Markov Decision Process(POMDP) environments. Conventional RL-methods, however, have limited applicability to POMDP To overcome the partial observability, several algorithms were proposed [5], [7]. The aim of this paper is to extend our previous algorithm for POMDP, called Labeling Q-learning(LQ-learning), which reinforces incomplete information of perception with labeling. Namely, in the LQ-learning, the agent percepts the current states by pair of observation and its label, and the agent can distinguish states, which look as same, more exactly. Labeling is carried out by a hash-like function, which we call Labeling Function(LF). Numerous labeling functions can be considered, but in this paper, we will introduce several labeling functions based on only 2 or 3 immediate past sequential observations. We introduce the basic idea of LQ-learning briefly, apply it to maze problems, simple POMDP environments, and show its availability with empirical results, look better than conventional RL algorithms.

• Journal of the Institute of Convergence Signal Processing
• /
• v.16 no.1
• /
• pp.1-8
• /
• 2015

In many image processing tasks, connected component labeling (CCL) is performed to extract regions of interest. CCL was usually done in a sequential fashion when image resolution was relatively low and there are small number of input channels. As image resolution gets higher up to HD or Full HD and as the number of input channels increases, sequential CCL is too time-consuming to be used in real time applications. To cope with this situation, parallel CCL framework was introduced where multiple cores are utilized simultaneously. Several parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method[1], modified 8 directional label selection (M8DLS) method[2], and HYBRID1 method[3]. Soh [3] showed that HYBRID1 outperforms NSZ-LE and M8DLS, and argued that HYBRID1 is by far the best. In this paper we propose an improved hybrid parallel CCL algorithm termed as HYBRID2 that hybridizes M8DLS with label backtracking (LB) and show that it runs around 20% faster than HYBRID1 for various kinds of images.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.10
• /
• pp.553-558
• /
• 2024

Morphological analysis involves segmenting morphemes, the smallest units of meaning or grammatical function in a language, and assigning part-of-speech tags to each morpheme. It plays a critical role in various natural language processing tasks, such as named entity recognition and dependency parsing. Much of modern natural language processing relies on deep learning-based language models, and Korean morphological analysis can be broadly categorized into sequence-to-sequence methods and sequential labeling methods. This study proposes a morphological analysis approach using the transformer encoder for sequential labeling to perform syllable-level part-of-speech tagging, followed by morpheme restoration and tagging through a pre-analyzed dictionary. Additionally, the CBOW method was used to extract syllable-level embeddings in lower dimensions, designing a lightweight morphological analyzer model with reduced parameters. The proposed model achieves fast inference speed and low parameter usage, making it efficient for use in resource-constrained environments.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.3
• /
• pp.217-226
• /
• 2003

A novel fingerprint ridge feature extraction using sequential labeling of thinned fingerprint image is proposed, which is invariant to position translation, scaling, and rotation. the proposed algorithm labels ridges of thinned fingerprint image sequentially using vertical line that goes through fingerprint core point. Then, we extract a feature from each labeled ridge and the extraction process is based on the type fo the ridge and a minutiae ridge angle in the ridge. The feature extracted through this process enables us to find out the kind of various minutiae and minutiae angle. As a result of the experiment using two thinned fingerprint images, we finally confirm that proposed algorithm is not related to position translation, scaling, and rotation.

• Toxicological Research
• /
• v.11 no.1
• /
• pp.127-131
• /
• 1995

Sequential changes in cell proliferation during the development of epitherial kidney tumors induced in rats were investigated by autoradiographic determination of the $^3H$-thymidine-labeling index. Renal cell tumors were induced in male Sprague-Dawley rats by oral administration of N-nitrosomorpholine at the concentration of 120 mg/l in the drinking water for 7 weeks. At different times between 12 and 34 weeks after withdrawal of the carcinogen (stop model) animals were sacrificed. According to cytological criteria, neoplastic lesions were classified into clear cell, acidophilic cell, basophilic cell and oncocytic tumors. The labeling index was found to be increased in all types of preneoplastic tubules as compared to their corresponding original tubules. A much stronger elevation of cell proliferation was ocurred during the development of renal cell tumors from preneoplastic tubules. Of four tumor types, acidophilic cell tumor showed the highest labeling index while oncocytoma exhibited the lowest proliferative activity. These findings are in good accordance with the clinical observations that acidophilic cell tumors have a worse prognosis than oncocytoma. The data presented in this study suggest that the individual proliferation rates may be an objective biological marker of kidney tumor aggressiveness.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.835-843
• /
• 2023

Given the structure of XML data, path and tree pattern matching algorithms play an important role in XML query processing. To facilitate decisions or relationships between nodes, nodes in an XML tree are typically labeled in a way that can quickly establish an ancestor-descendant on relationship between two nodes. However, these techniques have the disadvantage of re-labeling existing nodes or recalculating certain values if insertion occurs due to sequential updates. Therefore, in current labeling techniques, the cost of updating labels is very high. In this paper, we propose a new labeling technique called Fast XML encoding, which supports the update of order-sensitive XML documents without re-labeling or recalculation. It also controls the length of the label by reusing deleted labels at the same location in the XML tree. The proposed reuse algorithm can reduce the length of the label when all deleted labels are inserted in the same location. The proposed technique in the experimental results can efficiently handle order-sensitive queries and updates.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.9
• /
• pp.858-862
• /
• 2015

This paper presents a new forward-viewing mono-camera based obstacle detection algorithm for mobile robots. The proposed method extracts the coarse location of an obstacle in an image using inverse perspective mapping technique from sequential images. In the next step, graph-cut based image labeling is conducted for estimating the exact obstacle boundary. The graph-cut based labeling algorithm labels the image pixels as either obstacle or floor as the final outcome. Experiments are performed to verify the obstacle detection performance of the developed algorithm in several examples, including a book, box, towel, and flower pot. The low illumination condition, low color contrast between floor and obstacle, and floor pattern cases are also tested.

• Journal of Navigation and Port Research
• /
• v.39 no.4
• /
• pp.307-312
• /
• 2015

ARPA(Automatic Radar Plotting Aid) is a device to calculate CPA(closest point of approach)/TCPA(time of CPA), true course and speed of targets by vector operation of relative courses and speeds. The purpose of this study is to develop target acquisition and tracking technology for ARPA Radar implementation. After examining the previous studies, applicable algorithms and technologies were developed to be combined and basic ARPA functions were developed as a result. As for main research contents, the sequential image processing technology such as combination of grayscale conversion, gaussian smoothing, binary image conversion and labeling was deviced to achieve a proper target acquisition, and the NNS(Nearest Neighbor Search) algorithm was appllied to identify which target came from the previous image and finally Kalman Filter was used to calculate true course and speed of targets as an analysis of target behavior. Also all technologies stated above were implemented as a SW program and installed onboard, and verified the basic ARPA functions to be operable in practical use through onboard test.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.681-686
• /
• 2003

In this paper, we propose an algorithm to extract valid planar regions from stereo images for visual navigation of mobile robots. The algorithm is based on the difference image between the stereo images obtained by applying Homography matrix between stereo cameras. Illegal planar regions are filtered out by the use of labeling of the difference images and filtering of invalid blobs using the size of each blob. Also, illegal large planar regions such as walls are removed by adopting a weighted low-pass filtering of the difference image using the past difference images. The algorithms are experimented successfully by the use of stereo camera system built in a mobile robot and a PC-based real-time vision system.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.34 no.8
• /
• pp.301-307
• /
• 1985

The first four generations of computers are all based on a single basic design: the Von Neuman Processor, which is sequential and does one operation at a time. Efforts to develop concurrent or parallel computers have been carried on for many years. Data flow approach is significant in these efforts to make high speed parallel machines and expected a great deal of parallelism. In this paper we propose a preliminary data Flow Machine Model operating asynchronously on the base of Node Labelling. We introduce a concept of Node Labeling for this purpose which is relevant to the Data dependency and Parallelism. And we explain how the Node Tokens are fired in the proposed system.