Showing 1-25 of 52,082 resultsfor "Index Terms":Semantic Network
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Asymmetric Semantic Communication System Based on Diffusion Model in IoT
2023 IEEE 23rd International Conference on Communication Technology (ICCT)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
This paper presents an asymmetric semantic communication network based on the diffusion model for transmitting and recovering semantic information from images. The network employs a semantic segmentation model to extract semantic information from the images, generate desired images using the diffusion model. We compared end-to-end semantic communication networks with GAN-based semantic communicati...Show More
Impact of Using Semantic Social Networks on Organizations
2009 International Conference on Advances in Social Network Analysis and Mining
Year: 2009 | Conference Paper |
Cited by: Papers (1)
In a rapidly changing environment, a shift toward decentralized structure for organizations seems inevitable. Semantic Web technologies combined with social network analysis make the transition of a centralized organization to a decentralized one much easier. By increasing controllability and manageability of a decentralized structure, these tools can improve functionality and performance. A frame...Show More
Implementing the draft W3C semantic sensor network ontology
2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)
Year: 2010 | Conference Paper |
This paper examines the feasibility of using ontologies to model generic sensor networks, based on the capabilities of the current generation of ontology tools. The creation of such an ontology, the current tool's capacity to adequately maintain it, and its potential functionality, as part of a larger semantic system are addressed here. These topics were addressed by constructing a generic sensor ...Show More
Conceptual Approach in Structuring the Semantic Core Author's Text
2023 16th International Conference Management of large-scale system development (MLSD)
Year: 2023 | Conference Paper |
Proposed conceptual approach for the linguistic analysis author's text by structuring its semantic core with homogeneous and heterogeneous semantic networks, with a final synthesis based on the removal of semantic contradictions. Used semantic search and method for highlighting text topics of intellectual monitoring.Show More
Structures of Semantic Networks: Similarities between Semantic Networks and Brain Networks
2006 5th IEEE International Conference on Cognitive Informatics
Year: 2006 | Conference Paper |
Two networks were extracted from two large semantic networks, HowNet and synsets of WordNet, based on conceptual relations. Analysis of these networks shows that they are complex networks with features of small-world and scale-free. Results also show that semantic networks are similar to brain networks: (a) exponents of power law degree distributions are between 1.0 and 2.0, while exponents of bra...Show More
Schema Reasoning and Semantic Representation for Citation Semantic Link Network
2009 Third International Symposium on Intelligent Information Technology Application
Year: 2009 | Conference Paper |
Cited by: Papers (6)
Citation network lacks the semantics and can not reason. At present, research on citation network has mostly used scientometrics method combined with statistical physics and social network analysis approach to research and analyze citation network structure. The limited citation information is acquired, however, and efficiency is not high. In order to sufficiently and efficiently acquire citation ...Show More
Robust Semantic Communications for Speech Transmission
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2025 | Conference Paper |
In this paper, we propose a robust semantic communication system for speech transmission, named Ross-S2T, by delivering the essential semantic information. Specifically, we consider the speech-to-text translation (S2TT) as the transmission goal. First, a new deep semantic encoder is developed to convert speech in the source language to textual features associated with the target language, facilita...Show More
Multi-Element Features Extraction from High Spatial Resolution Remote Sensing Image Based on Semantic Segmentation Network
2024 International Conference on New Trends in Computational Intelligence (NTCI)
Year: 2024 | Conference Paper |
The high spatial resolution remote sensing image contains rich special information with a great detail. Traditional segmentation methods have low classification accuracy, the complexity of high spatial resolution remote sensing images also requires higher the classification technology of remote sensing images. In recent years, neural networks have made remarkable achievements in the field of image...Show More
A novel semantic segmentation method based on improved FCN for unmanned driving
2023 IEEE 6th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Driverless semantic segmentation is one of the research hotspots in the field of computer vision in recent years. Therefore, this paper proposes an unmanned semantic segmentation method based on improved fully convolutional network. Based on the FCN model, this paper uses HRNet to replace the backbone network. HRNet adopts high-resolution feature fusion method to ensure the output of high-resoluti...Show More
Research on IC-LOGO Extraction Algorithm Based on Deep Semantic Segmentation Network
2024 6th International Conference on Artificial Intelligence and Computer Applications (ICAICA)
Year: 2024 | Conference Paper |
Considering the characteristics of the logo and character areas being intertwined, along with the variability in size and irregularity in shape of logos within integrated circuit (IC) identification images, this paper propose a logo extraction algorithm based on a deep semantic segmentation network. Initially, preprocessing and data augmentation techniques are employed to facilitate the creation o...Show More
Semantic Communication: A Survey on Research Landscape, Challenges, and Future Directions
Amid the global rollout of fifth-generation (5G) services, researchers in academia, industry, and national laboratories have been developing proposals for the sixth-generation (6G), whose materialization is fraught with many fundamental challenges. To alleviate these challenges, a deep learning (DL)-enabled semantic communication (SemCom) has emerged as a promising 6G technology enabler, which emb...Show More
A Context Centric Approach for Semantic Image Annotation and Retrieval
2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns
Year: 2009 | Conference Paper |
Cited by: Papers (2)
In this preliminary research, we discuss techniques to improve the quality of image retrieval and image management with the help of context information over the Web. Our hypothesis is that leveraging the semantic annotated contextual metadata of the image would yield the relevant search results and facilitate building a consistent, unambiguous image knowledge base. Inferencing capability of semant...Show More
Exploring FMU-NET: A Comprehensive Study on Person Identification Through Novel Semantic Segmentation Techniques
2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
Year: 2023 | Conference Paper |
The paper proposes novel face semantic segmentation for person identification. Various face segmentation procedures are used to analyze the accuracy of the model to learn specific patterns from the annotated masks. The FMU- Net, a simplistic semantic segmentation model, amalgamates components from both the Residual U-Net and Mobile U-Net architectures. It adeptly capitalizes on the strengths of th...Show More
Daytime to Night Image Translation Based on Semantic Segmentation
2023 IEEE International Conference on Sensors, Electronics and Computer Engineering (ICSECE)
Year: 2023 | Conference Paper |
Image-to-image translation is the process of converting images from one domain to another. The goal of image-to-image translation is to learn the mapping between input and output images. In the face of complex scenes, for example, when the field changes greatly from day to night, the daytime image scenes have complex semantic information, which makes it difficult for convolutional neural networks ...Show More
Learning Spatiotemporal Features for Video Semantic Segmentation Using 3D Convolutional Neural Networks
2022 6th International Symposium on Computer Science and Intelligent Control (ISCSIC)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
In recent years, significant progress has been made in still image segmentation. However, applying these advanced algorithms to each video frame requires extensive calculation. In this paper, we made two main contributions. The first contribution is a new dataset, we made a human semantic segmentation video dataset based on the Refer-YubeVOS dataset. It provides a benchmark for evaluating video se...Show More
Dynamic Change of Services in Wireless Sensor Network Middleware Based on Semantic Technologies
2010 Sixth International Conference on Autonomic and Autonomous Systems
Year: 2010 | Conference Paper |
Cited by: Papers (4)
This paper presents a middleware for Wireless Sensor Networks that uses a set of technical statements, such as patterns and styles, in order to achieve flexibility, autonomy and adaptation. The middleware exposes the functionality of the network as Semantic Web Services, so that applications can access its functionality through Web Services. The Service-oriented architecture is used as a means of ...Show More
An Adaptive Deep Neural Network for Detection, Recognition of Objects with Long Range Auto Surveillance
2018 IEEE 12th International Conference on Semantic Computing (ICSC)
Year: 2018 | Conference Paper |
Cited by: Papers (7)
Automatic detection and recognition of predefined objects in a video stream of Long Range Surveillance Systems is multidimensional problem regarding the complexity of the background, moving sensor(s) and low probability pattern recognition of targets. An Adaptive Fuzzy based Network topology is proposed in this paper which is used in parallel with Deep Convolutional Neural Networks (DCNNs). In ord...Show More
Lightweight and Efficient Convolutional Neural Network for Road Scene Semantic Segmentation
2022 IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Recently, Intelligent Transportation Systems (ITS) have become one of the most important fields of research topics, while it provides advanced road scene monitoring. Actually, computer vision is one of the most widely used fields in ITS, while it offers various tasks, such as object detection, image classification, and segmentation. Besides, Convolutional Neural Networks (CNNs) have shown their ef...Show More
Recognition and Extraction of Part Image Based on Convolutional Neural Network
2024 IEEE 6th International Conference on Power, Intelligent Computing and Systems (ICPICS)
Year: 2024 | Conference Paper |
The traditional mechanical parts image contour recognition and extraction method is inefficient and the applicable object has limitations. In today, intelligent and automation can not meet the requirements of production development in the field of machinery, neural network technology has the advantages of high efficiency, high precision and low cost, to solve many problems in the field of machiner...Show More
A mobile spontaneous semantic P2P system
2009 IEEE International Conference on Communications Technology and Applications
Year: 2009 | Conference Paper |
The WWW is often used as synonym for the Internet. In the last 20 years the Web became the Internet application. And it evolves. There is the Web 2.0 mobile Web, semantic Web. Though, a noteworthy number of data are sent over short distances, the mobile Web is usually based on a public land mobile network. This is a tremendous was of resource and adds unnecessarily entities which can fail. Spontan...Show More
Structural Determination of Ontology-Driven Trust Networks in Semantic Social Institutions and Ecosystems
International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM'07)
Year: 2007 | Conference Paper |
Cited by: Papers (6)
Social institutions and ecosystems are growing across the web and social trust networks formed within these systems create an extraordinary test-bed to study relation dependant notions such as trust, reputation and belief. In order to capture, model and represent the semantics of trust relationships forming the trust networks, main components of relationships are represented and described using on...Show More
A Survey of Semantic Segmentation Methods in Traffic Scenarios
2022 International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM)
Year: 2022 | Conference Paper |
Cited by: Papers (5)
Semantic segmentation has always been a very challenging research topic in computer vision and deep learning and has extensive applications in real-life scenarios. With the development of computing hardware and deep learning technology, researchers have a higher research enthusiasm for semantic segmentation. This work briefly introduces several semantic segmentation models, datasets, and the main ...Show More
SWINT-RESNet: An Improved Remote Sensing Image Segmentation Model Based on Transformer
Deep neural networks have been widely used in remote sensing image segmentation. Nowadays, artificial intelligence methods are increasingly applied to remote sensing feature classification. Although convolutional neural networks (CNNs) are widely used for image segmentation tasks, their global feature extraction with increasing image samples is insufficient. Furthermore, transformer is now being f...Show More
SRRM: Semantic Region Relation Model for Indoor Scene Recognition
2023 International Joint Conference on Neural Networks (IJCNN)
Year: 2023 | Conference Paper |
Cited by: Papers (6)
Despite the remarkable success of convolutional neural networks in various computer vision tasks, recognizing indoor scenes still presents a significant challenge due to their complex composition. Consequently, effectively leveraging semantic information in the scene has been a key issue in advancing indoor scene recognition. Unfortunately, the accuracy of semantic segmentation has limited the eff...Show More
Application of the Semantic Segmentation Method in the Assessment of Forest Carbon Balance
2023 16th International Conference Management of large-scale system development (MLSD)
Year: 2023 | Conference Paper |
This article focuses on the problem of human impact on the natural environment and its solution by machine learning methods. The concept of carbon balance is key in assessing climate change on the planet, which is especially important in connection with global warming. The main causes of global warming are associated with anthropogenic emissions of carbon dioxide as a result of agricultural produc...Show More
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