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Pattern Recognition and Tracking XXXIV 2023

作者： Chen, Yan Gong, Wenhui Alam, Mohammad S. Sang, Jun School of Big Data & Software Engineering Chongqing University Chongqing401331 China Department of Electrical Engineering and Computer Science Texas A&M University - Kingsville KingsvilleTX78363-8202 United States

ISBN: (数字)9781510661691

ISBN: (纸本)9781510661684

Makeup transfer aims to extract a specific makeup from a face and transfer it to another face, which can be widely used in portrait beauty, and cosmetics marketing. At present, existing methods can achieve the transfer of the entire facial makeup, but the quality of makeup transfer is not excellent because there may be a mismatch between the two images. In this paper, we propose a facial makeup transfer network based on the Laplacian pyramid, which can better preserve the facial structure from the source image and achieve high-quality transfer results. The model consists of three parts: makeup feature extraction, facial structure feature extraction, and makeup fusion. The makeup extraction part is used to extract the facial makeup from the reference image. And the facial structure feature extraction part is used to extract facial structure from the source image, in order to solve the loss of facial details when extracting facial structural features, we used the method based on Laplacian Pyramid. The makeup fusion part will fuse the facial makeup with facial structure features. Many experiments on the MT dataset have shown that this method can transfer makeup successfully without changing the original facial structure, and achieve advanced performance in various makeup styles. © 2023 SPIE.

关键词： Feature extraction

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Anomaly Detection in Spatial Information Networks: A Security Knowledge Graph-based Approach

Anomaly Detection in Spatial Information Networks: A Securit...

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Intelligent Computing and Robotics (ICICR), International Conference on

作者： Yayue Tan Yaqi Zhang Hui Liu Yongqing Tang College of Computer and Information Science School of Software Southwest University Chongqing China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350372274

ISBN: (纸本)9798350372281

Anomaly detection stands as a critical element in securing space information networks (SINs). This paper delves into the realm of anomaly detection within dynamic networks, shedding light on established methodologies. The focus lies on scrutinizing various anomaly detection strategies in space information networks, conducting a comprehensive assessment of their practical applications, advantages, and drawbacks. Moreover, it introduces a novel anomaly detection approach driven by deep learning principles. This innovative method merges graph convolution techniques with a network security-oriented knowledge graph, presenting a cutting-edge solution. As a final contribution, the paper extends its purview to the future landscape of anomaly detection within space information networks, offering valuable insights into potential advancements and forthcoming trends in this domain. This holistic investigation seeks to enhance the understanding of anomaly detection paradigms within the unique context of space information networks, aiming to fortify their security measures and operational resilience.

关键词： Knowledge engineering Convolution Network topology Knowledge graphs Market research computer security Anomaly detection

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Model Predictive Control for Automated Network Assurance in Intent-Based Networking enabled Service Function Chains 36

Model Predictive Control for Automated Network Assurance in ...

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36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Avgeris, Marios Leivadeas, Aris Athanasopoulos, Nikolaos Lambadaris, Ioannis Falkner, Matthias Carleton University Department of Systems and Computer Engineering Ottawa Canada Ácole de Technologie Supérieure Department of Software and It Engineering Montreal Canada Queen's University School of Electronics Electrical Engineering and Computer Science Belfast United Kingdom Cisco Systems Ottawa Canada

ISBN: (纸本)9781665477161

Recent trends in Network Function Virtualization (NFV) combined with Internet of Things (IoT) and 5G applications have reshaped the network service offering. In particular, Service Function Chains (SFCs) can associate network functions with physical and virtual resources towards providing a complete network service. Concurrently, the management of a continuously expanding network and the fulfillment of the applications' requirements pave the way for autonomic network solutions. Intent Based Networking (IBN) is a novel paradigm that aims to achieve the automatic orchestration of network services and the assurance of their performance. Accordingly, in this paper, we propose a novel automated network assurance model, based on Model Predictive Control, to guarantee the Quality of Service (QoS) and security requirements of multi-tenant and IBN-enabled SFCs. In this context, corrective decisions are proactively taken, in the form of incoming intent relocations among the SFCs. The results reveal that our model can assure with high probability the application requirements and minimize QoS violations. © 2023 IEEE.

关键词： Network function virtualization

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Real-time crowd counting via mobile-friendly Vision Transformer network 34

Real-time crowd counting via mobile-friendly Vision Transfor...

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Pattern Recognition and Tracking XXXIV 2023

作者： Ji, Peirong Wu, Zhiwei Chen, Yan Alam, Mohammad S. Sang, Jun School of Big Data & Software Engineering Chongqing University Chongqing401331 China Department of Electrical Engineering and Computer Science Texas A&M University - Kingsville KingsvilleTX78363-8202 United States

ISBN: (数字)9781510661691

ISBN: (纸本)9781510661684

Accurate crowd counting in congested scenes remain challengeable in the trade-off of efficiency and generalization. For solving this issue, we propose a mobile-friendly solution for the network deployment in high response speed demand scenarios. In order to introduce the profound potential of global crowd representations to lightweight counting model, this work suggests a novel crowd counting aimed mobile vision transformers architecture (CCMTNet), which strives for enhancing the efficiency of the model universality in real-time crowd counting tasks on resource constrained computing devices. The framework of linear CNN network interpolation structure with self-attention blocks endows the model with the ability of local feature extraction and global high-dimensional crowd information processing with low computational cost. In addition, several experimental networks with different scales based on the proposed architecture are comprehensively verified to balance the accuracy loss as compressing the computing costs. Extensive experiments on three mainstream datasets for crowd counting tasks well demonstrate the effectiveness of this proposed network. Particularly, CCMTNet achieves the feasibility of reconciling the counting accuracy and efficiency in comparisons with traditional lightweight CNN networks. © 2023 SPIE.

关键词： Efficiency

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General or Specific? Retrofitting AI and IoT-Enabled Hydroponic Grow Tents for Use in Different Climates Across Rural Africa

General or Specific? Retrofitting AI and IoT-Enabled Hydropo...

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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Sarina Till Taryn Wilson Rikurora Karamata Franco Beukes Metaramuje Kaundje Heike Winschiers-Theophilus School of Computer Science IIE Durban South Africa Software Engineering NUST Windhoek Namibia

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

Climate change threatens African subsistence farming with erratic rainfall, droughts, and seasonal shifts causing devastating crop failures. Hydroponic farming, often recommended to mitigate these threats, requires constant monitoring and knowledge, which can be overwhelming for first-time growers. Research has explored using the Internet of Things (IoT) and Artificial Intelligence (AI) to automate and monitor hydroponic systems. Still, few studies have tested these systems in the field with farmers. Our previous work involved an eight-month deployment of an AI and IoT-enabled hydroponic system with rural subsistence farmers in South Africa. We conducted focus groups and observed the hydroponic systems using a qualitative approach. This paper discusses lessons learned from deploying the system in Namibia. We found that generalized AI models are unlikely to succeed due to differences in water quality, climate, participant readiness, and internet connectivity. Therefore, AI and IoT systems for rural Africa must be tailor-made to be functional and effective for crop growth.

关键词： Computational modeling Hydroponics Crops Africa Water quality Internet of Things Artificial intelligence Monitoring Farming Context modeling

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Nexus: Efficient and Conflict-Equivalent DAG-Based Permissioned Blockchain Sharding

Nexus: Efficient and Conflict-Equivalent DAG-Based Permissio...

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International Workshop on Quality of Service

作者： Yuchao Zhang Xiaotian Wang Xiaofeng He School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350350128

ISBN: (纸本)9798350350135

Sharding is one of the most promising solutions to tackle the well-known scalability issue in blockchain by dividing the network into multiple parallel committees. However, inefficient and insecure handling of cross-shard transactions can lead to a decline in the system service quality. Existing permissioned blockchains are mainly based on the classic two-phase commit (2PC) and two-phase locking (2PL) from traditional distributed databases to implement cross-shard transactions with deterministic safety, but this also leads to issues such as decreased system throughput and frequent transaction aborts. In this paper, we introduce Nexus, an efficient and conflict-equivalent sharded permissioned blockchains to overcome the aforementioned challenges. The core idea of Nexus is to construct a directed acyclic graph (DAG) among all shards to establish a partial order of blocks, while leaving transaction dissemination and final ordering to be completed in parallel by each shard. Nexus alleviate the overhead of global ordering through a efficient consensus process, and ensure that all transactions with overlapping read and write sets can be committed in the same relative order across different shards. A prototype of Nexus is implemented and evaluated, and experimental results show that Nexus achieves approximately 70% and 50% throughput improvement over AHL and SharPer under default settings.

关键词： Sharding Directed acyclic graph Protocols Scalability Prototypes Quality of service Throughput

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Innovative and affordable wearable solution for suppression of hand tremors

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International Journal of Intelligent Systems Technologies and Applications 2021年第3期20卷 233-244页

作者： Vishnu, Dana Vasudevan, Shriram K. Dhanush, G.A. Siddharth, S. Raj, Kiran S. Department of Computer Science and Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Software Services MNC Bengaluru India

Hand tremor influences a huge number of individuals around the world. Tremor is characterised as unintended, cadenced muscle development. Albeit most tremors neither reason serious medical issues nor threaten life, most patients experience many troubles in performing everyday exercises. It is humiliating to numerous individuals, particularly more seasoned people. Tremor negatively affects personal satisfaction and decreases the ability to perform everyday life undertakings such as eating, drinking, writing, and changing clothing. Some patients with mild tremor do not visit doctors if tremor does not hinder their daily life activities. Their situations often worsen over time. There is currently very few to almost no external solution existing to cope with this medical condition. We have developed a glove that is able to dynamically conceive the motion of a user’s hand and ascertain the difference between intentional movement and unintentional movement. Further, we have quantified, verified and attempted to provide a haptic response to the users’ fingers with the help of coin motors to help counteract the unwanted vibration. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Internet of things

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Delivery Time Prediction Using Large-Scale Graph Structure Learning Based on Quantile Regression 39

Delivery Time Prediction Using Large-Scale Graph Structure L...

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Zhang, Lei Zhou, Xin Zeng, Zhiwei Cao, Yiming Xu, Yonghui Wang, Mingliang Wu, Xingyu Liu, Yong Cui, Lizhen Shen, Zhiqi Shandong University School of Software Jinan China Jinan China Alibaba-NTU Singapore Joint Research Institute Singapore Nanyang Technological University School of Computer Science and Engineering Singapore Alibaba Group China

ISBN: (纸本)9798350322279

Predicting Estimated Time of Arrival (ETA) for packages is a critical problem in e-commerce. The prediction is often made based on spatial (sending and receiving addresses), temporal (payment time), and context (merchants) attributes. Existing methods usually formalize this task as an Origin-Destination (OD) ETA prediction problem and exploit the attribute relations with graph learning. However, most existing methods make use of fixed and manually defined graph structures, which are often not optimal for downstream ETA task and hence lead to unsatisfactory prediction results. In addition, current ETA models tend to focus on prediction accuracy without considering fulfillment rate. This may lead to a low fulfillment rate in practice, i.e., actual delivery time is much longer than estimations provided by models, which consequently exacerbates the frustrating experiences for users. To address these issues, we propose a novel Graph Structure Learning-based Quantile Regression (GSL-QR) model for e-commerce ETA prediction in this paper. Specifically, we utilize graph structure learning to dynamically update the spatial and temporal relation graphs of orders and learn optimal graph structures and graph embeddings guided by downstream ETA prediction task. To guarantee both prediction accuracy and order fulfillment rate, we design a multi-objective quantile regression in GSL-QR that can find the Pareto solution of the problem. In order to extend GSL to large-scale real-world graphs, we devise a Fast Sampling-based Graph Structure Learning (FS-GSL) method, which can significantly reduce the computational complexity of graph structure learning. Finally, we conduct comprehensive experiments on three industrial datasets collected from Alibaba e-commerce platform. The results demonstrate that the proposed model can significantly outperform baselines on both ETA prediction accuracy and order fulfillment rate. © 2023 IEEE.

关键词： Graphic methods

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Flexible Capacitive Pressure Sensors and Their Applications in Human-Machine Interactions 2

Flexible Capacitive Pressure Sensors and Their Applications ...

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2nd International Symposium on Sensor Technology and Control, ISSTC 2023

作者： Fang, Chenyu Fu, Tianli Shi, Yao Changzhou No.1 High School Changzhou China Wuhan University of Technology School of Mechanical and Electronic Engineering Wuhan China Southwest University College of Computer and Information Science College of Software Chongqing China

ISBN: (纸本)9798350314465

Flexible capacitive pressure sensors have shown excellent application potential in human-machine interactions, wearable electronic devices, biological and medical, and electronic skin. Compared with piezoresistive and piezoelectric pressure sensors, capacitive pressure sensors with advantages such as high flexibility, high stability, low consumption, and simple construction. Because of these advantages, flexible capacitive pressure sensors have become the key research direction of pressure sensors in recent years. This paper introduces the working principle of flexible capacitive pressure sensors and discusses numerous research on improving the performance of flexible capacitive pressure sensors. Then two methods of improving the dielectric layer structures to improve the sensitivity of the sensor and some related works are reviewed. Finally, the flexible capacitive pressure sensors' huge potential for advances in human-machine interactions areas such as health care and motion monitoring is also discussed. The paper concludes with an overview of future research directions of improving the performance of flexible capacitive pressure sensors. © 2023 IEEE.

关键词： Pressure sensors

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Depth Completion using Galerkin Attention

Depth Completion using Galerkin Attention

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yinuo Xu Xuesong Zhang School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Current depth completion methods usually employ a pair of calibrated RGB and depth sensors to reconstruct a dense depth map. Although RGB (dense) and depth (sparse) measurements are collected from the same underlying scene, they reflect different physical characteristics and thus it remains rather intricate how the devised RGB guidance scheme can effectively leads to a faithful depth recovery. Different from existing 3D geometry representations, such as point cloud, voxels or meshes, we propose to define 3D scenes as vector-valued functions, f : Ω ∋ (u, v) ↦ (r, g, b, d) ∈ ℝ 4 , mapping from the image plane Ω to RGBD vectors. This scene function representation brings two benefits: 1) allowing for the adaptation of the Galerkin method to explore the nodal basis of the scene function space, and 2) transforming the irregularly scattered (X, Y, Z) points in the Euclidean space into the depth function defined over the regular grid in the image plane. We further leverage these two benefits within a deep neural network, characterized by an efficient Galerkin attention-based RGBD function embedding to effectively explore the interaction of color and depth information, and by the utilization of equivariant convolution operation on the RGBD feature map as efficient basic blocks. Experiments show that the proposed method achieves significant performance improvement over state-of-the-arts. Code at https://***/ZXS-Labs/DCGA.

关键词： Point cloud compression Geometry Three-dimensional displays Image color analysis Sensor phenomena and characterization Vectors Encoding Method of moments Intelligent robots Image reconstruction

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