• Title/Summary/Keyword: graph encoding

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A Study about Learning Graph Representation on Farmhouse Apple Quality Images with Graph Transformer (그래프 트랜스포머 기반 농가 사과 품질 이미지의 그래프 표현 학습 연구)

  • Ji Hun Bae;Ju Hwan Lee;Gwang Hyun Yu;Gyeong Ju Kwon;Jin Young Kim
    • Smart Media Journal
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    • v.12 no.1
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    • pp.9-16
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    • 2023
  • Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

Creating 3D Artificial Flowers using Structured Directed Graph and Interactive Genetic Algorithm (구조적 방향성 그래프와 대화형 유전자 알고리즘을 이용한 3차원 꽃의 생성)

  • 민현정;조성배
    • Journal of KIISE:Software and Applications
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    • v.31 no.3
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    • pp.267-275
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    • 2004
  • Directed graph and Lindenmayer system (L-system) are two major encoding methods of representation to develop creatures in application field of artificial life. It is difficult to define real morphology structurally using the L-systems which are a grammatical rewriting system because L-systems represent genotype as loops, procedure calls, variables, and parameters. This paper defines a class of representations called structured directed graph, which is identified by its ability to define structures of the genotype in the translation to the phenotype, and presents an example of creating 3D flowers using a directed graph which is proper method to represent real morphology, and interactive genetic algorithm which decodes the problem with human's emotional evaluation. The experimental results show that natural flower morphology can be generated by the proposed method.

CoNSIST : Consist of New methodologies on AASIST, leveraging Squeeze-and-Excitation, Positional Encoding, and Re-formulated HS-GAL

  • Jae-Hoon Ha;Joo-Won Mun;Sang-Yup Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2024.05a
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    • pp.692-695
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    • 2024
  • With the recent advancements in artificial intelligence (AI), the performance of deep learning-based audio deepfake technology has significantly improved. This technology has been exploited for criminal activities, leading to various cases of victimization. To prevent such illicit outcomes, this paper proposes a deep learning-based audio deepfake detection model. In this study, we propose CoNSIST, an improved audio deepfake detection model, which incorporates three additional components into the graph-based end-to-end model AASIST: (i) Squeeze and Excitation, (ii) Positional Encoding, and (iii) Reformulated HS-GAL, This incorporation is expected to enable more effective feature extraction, elimination of unnecessary operations, and consideration of more diverse information, thereby improving the performance of the original AASIST. The results of multiple experiments indicate that CoNSIST has enhanced the performance of audio deepfake detection compared to existing models.

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Implementation of SOAP Client in U Programming Environment (nML 프로그래밍 환경에서 SOAP 클라이언트 구현)

  • 권오경;한태숙
    • Journal of KIISE:Software and Applications
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    • v.30 no.1_2
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    • pp.164-172
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    • 2003
  • Web service implementations are now rapidly growing. Web services are easily achieved by XML messaging for most programming languages. Applications usually utilize web services through APIs tied to a specific implementation of SOAP. nML is a dialect of SML and OCaml made in ROPAS. The soaptype type in nML is defined for the value of SOAP encoding. SOAP encoding specification defines rules for serialization of a graph of typed objects using XML Schema. XML Schema validates XML SOAP value. The soaptype type is encoded to XML and decoded from XML. It is necessary to guarantee safe encoding and decoding. So, the definitions for element and type definition in XML Schema are specified by element type and typeinfo type, which include the part of the definitions of XML Schema specification.

Path-Based Computation Encoder for Neural Architecture Search

  • Yang, Ying;Zhang, Xu;Pan, Hu
    • Journal of Information Processing Systems
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    • v.18 no.2
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    • pp.188-196
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    • 2022
  • Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

Semi-supervised learning using similarity and dissimilarity

  • Seok, Kyung-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.1
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    • pp.99-105
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    • 2011
  • We propose a semi-supervised learning algorithm based on a form of regularization that incorporates similarity and dissimilarity penalty terms. Our approach uses a graph-based encoding of similarity and dissimilarity. We also present a model-selection method which employs cross-validation techniques to choose hyperparameters which affect the performance of the proposed method. Simulations using two types of dat sets demonstrate that the proposed method is promising.

Provenance Compression Scheme Considering RDF Graph Patterns (RDF 그래프 패턴을 고려한 프로버넌스 압축 기법)

  • Bok, kyoungsoo;Han, Jieun;Noh, Yeonwoo;Yook, Misun;Lim, Jongtae;Lee, Seok-Hee;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.16 no.2
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    • pp.374-386
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    • 2016
  • Provenance means the meta data that represents the history or lineage of a data in collaboration storage environments. Therefore, as provenance has been accruing over time, it takes several ten times as large as the original data. The schemes for effciently compressing huge amounts of provenance are required. In this paper, we propose a provenance compression scheme considering the RDF graph patterns. The proposed scheme represents provenance based on a standard PROV model and encodes provenance in numeric data through the text encoding. We compress provenance and RDF data using the graph patterns. Unlike conventional provenance compression techniques, we compress provenance by considering RDF documents on the semantic web. In order to show the superiority of the proposed scheme, we compare it with the existing scheme in terms of compression ratio and the processing time.

Inter-frame vertex selection algorithm for lossy coding of shapes in video sequences (동영상에서의 모양 정보 부호화를 위한 정점 선택 알고리즘)

  • Suh, Jong-Yeul;Kim, Kyong-Joong;Kang, Moon-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.4
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    • pp.35-45
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    • 2000
  • The vertex-based boundary encoding scheme is widely used in object-based video coding area and computer graphics due to its scalability with natural looking approximation. Existing single framebased vertex encoding algorithm is not efficient for temporally correlated video sequences because it does not remove temporal redundancy. In the proposed method, a vertex point is selected from not only the boundary points of the current frame but also the vertex points of the previous frame to remove temporal redundancy of shape information in video sequences. The problem of selecting optimal vertex points is modeled as finding shortest path in the directed acyclic graph with weight The boundary is approximated by a polygon which can be encoded with the smallest number of bits for maximum distortion. The temporal redundancy between two successive frames is efficiently removed with the proposed scheme, resulting in lower bit-rate than the conventional algorithms.

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Implementation of Algebra and Data Model based on a Directed Graph for XML (방향 그래프 기반 XML 데이터 모델과 대수 구현)

  • Park, Seong-Hui;Choe, Eun-Seon;Ryu, Geun-Ho
    • The KIPS Transactions:PartD
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    • v.8D no.6
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    • pp.799-812
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    • 2001
  • As XML become more popular for encoding data and exchanging format on the web, recent work on processing XML Document in DBMS has been performed. However, there is no formal data model for XML, and there is lack of research on XML algebra for processing complex XML query and even the mediators have many restrictions. Therefore, this paper proposes formal data model and algebra based on directed edge labeled graph for XML query. To implement algebra, not only algorithms of operation for algebra are presented, but also they are implemented using access method and path index based on RDBMS or ORDBMS. In particular, experiments to show the effectiveness of the implemented algebra are performed on XML documents on EST data which are semistructured data.

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Merging of Topological Map and Grid Map using Standardized Map Data Representation (표준화된 지도 데이터 표현방법을 이용한 위상지도와 격자지도의 병합)

  • Jin, Hee-Seon;Yu, Wonpil;Moon, Hyungpil
    • The Journal of Korea Robotics Society
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    • v.9 no.2
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    • pp.104-110
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    • 2014
  • Mapping is a fundamental element for robotic services. There are available many types of map data representation such as grid map, metric map, topology map, etc. As more robots are deployed for services, more chances of exchanging map data among the robots emerge and standardization of map data representation (MDR) becomes more valuable. Currently, activities in developing MDR standard are underway in IEEE Robotics and Automation Society. The MDR standard is for a common representation and encoding of the two-dimensional map data used for navigation by mobile robots. The standard focuses on interchange of map data among components and systems, particularly those that may be supplied by different vendors. This paper aims to introduce MDR standard and its application to map merging. We have applied the basic structure of the MDR standard to a grid map and Voronoi graph as a kind of topology map and performed map merging between two different maps. Simulation results show that the proposed MDR is suitable for map data exchange among robots.