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Design of Bird Repellent System Based on Machine Vision Detection and Localization 4

Design of Bird Repellent System Based on Machine Vision Dete...

引用

4th IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Jiang, Zhizhe Zhang, Yuechong Liu, Mingyang Qu, Zenghui Liu, Haiying Deng, Lixia Liu, Lida Li, Shuang Qilu University of Technology Shandong Academy of Sciences School of Information and Automation Engineering Jinan250353 China Shandong Runyi Intelligent Technology Co. Ltd. Jinan250002 China

ISBN: (纸本)9798350361643

Bird strike phenomenon generally refers to incidents where aircraft structural damage due to collisions with birds during low-altitude flight. Such incidents can lead to accidents, casualties, and economic losses. the civil aviation industry has attached great importance to bird strike prevention, devising regulations and standards to mitigate bird strike risks through scientific management and measures. Machine vision bird repellent systems, an environmentally friendly and non-contact method, align with current environmental trends. this paper comprehensively employed and fused traditional YOLOv5, KCF, Haarcascade, and Adaboost for target recognition and tracking. It proposes constructing a visual gimbal using a Raspberry Pi, servos, camera, etc. Python programming language is utilized to implement multi-mode bird identification within the field of view and issue voice alerts to ground control personnel promptly upon bird detection. the tracking device is activated according to predetermined conditions to efficiently and accurately handle bird situations. the designed system can accurately identify and track birds, thereby helping to reduce the probability of bird strike incidents and enhance flight safety. © 2024 IEEE.

关键词： Computer vision

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Analysis of Extreme Rainstorm in Zhengzhou, Henan and derivative issues 4

Analysis of Extreme Rainstorm in Zhengzhou, Henan and deriva...

引用

4th international conference on Geoscience and Remote Sensing Mapping, GRSM 2022

作者： Ji, Zhishi Ling, Guorong Liu, Jiaming Zhao, Jinying College of Art and Science Department of Atmosphere Science Ohio State University ColumbusOH United States School of Atmospheric Sciences Sun Yat-sen University Zhuhai China Nanjing University of Information Science and Technology Atmospheric Science China College of Agricultural Science The Pennsylvania State University State CollegePA United States

ISBN: (数字)9781510662179

ISBN: (纸本)9781510662162

In this paper, the extreme rainstorm in Zhengzhou, Henan is analysed. First of all, a brief overview of the flood in Zhengzhou Henan is introduced. Secondly, the definition of rainstorm and flood is discussed. thirdly, the factors affecting the frequency of floods in Henan province and specifically the uniqueness of this flood in Zhengzhou is investigated. Finally, some suggestions are provided to reduce the harm of extreme rainstorm to minimum. © 2023 SPIE.

关键词： Floods

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A New Sight to Optimize the Layout of Wave Energy Converters 4

A New Sight to Optimize the Layout of Wave Energy Converters

引用

4th international conference on Computer engineering and Application, ICCEA 2023

作者： Zhang, Zihang Lei, Zhenyu Jin, Ting Li, Jiayi Todo, Yuki Gao, Shangce University of Toyama Faculty of Engineering Toyama930-8555 Japan School of Science Nanjing Forestry University Nanjing210037 China Kanazawa University Faculty of Electrical Information and Communication Engineering Ishikawa9201192 Japan

ISBN: (纸本)9798350347548

Renewable energies are playing an increasingly important role in sustainable advancement. Wave energy has received a lot of attentions from researchers in recent years owing to its enormous potential and its minimal impact on aquatic organisms. the previous research has found that there are many factors that influence the generation of wave energy converters (WECs), such as PTO, layout, wave conditions etc. However, the energy output of WECs still is limited in large wave farm, due to the limitation of positions of an array of fully submerged three- tether buoy. In this study, we propose an improved algorithm based on multilayer information transfer for optimizing the farm layout of the wave energy converters and compare it with state-of- the-art methods applied to the WEC problem. Experiments are designed for the oscillating buoy-type wave energy converters in four real-wave scenarios (Perth, Adelaide, Tasmania, and Sydeny), using the numerical model to calculate the energy output of wave energy converters. the experimental results show that our improved strategy is highly competitive. © 2023 IEEE.

关键词： Aquatic organisms

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Domain Adaptation based on Attention-Weighted Optimal Transport and Cluster Alignment 4

Domain Adaptation based on Attention-Weighted Optimal Transp...

引用

4th international conference on Computer Vision, Image and Deep Learning, CVIDL 2023

作者： Zhu, Yanan Qi, Yangyang College of Computer Engineering and Science Shanghai University Shanghai China

ISBN: (纸本)9798350326444

Optimal transport (OT) as an efficient way to measure differences in distribution. provide new ideas for solving the unsupervised domain adaptation (UDA) problem. However, existing work based on OT ignores the multi-modal structure of the domain and does not adequately reflect the true data distribution. therefore, this paper proposes a new deep UDA framework, namely attention-weighted optimal transport and cluster alignment (AWOT). Specifically, the model first proposes a weighting strategy based on a self-attentive mechanism to reduce the bias caused by mini-batch selection in training. the strategy calculates weights by correlating the iterative prediction results of the source and target domains to weight the optimal in-transmission cost function. A confidence thresholding technique is also proposed to filter out low confidence target samples to enhance the robustness of pseudo-label. Moreover, AWOT is also equipped with a clustering centroid alignment loss to learn discriminative features. Comprehensive experiments have shown that AWOT outperforms existing state-of-the-art methods on several domain adaptation benchmarks. © 2023 IEEE.

关键词： Alignment

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Co-REX:A Collaborative Transformer for Try Location Detection and Catch Exception Prediction 36

Co-REX:A Collaborative Transformer for Try Location Detectio...

引用

36th international conference on Software engineering and Knowledge engineering, SEKE 2024

作者： Xiao, Jing Liang, Tianyu School of Computer Science South China Normal University Guangzhou China School of Artificial Intelligence South China Normal University Foshan China

ISBN: (纸本)1891706594

Try Location Detection (TLD) and Catch Exception Prediction (CEP) are two interrelated tasks in runtime exception handling which is a crucial aspect in Java programming. the performance of each task can significantly benefit from the information provided by the other. However, previous methods primarily treated these tasks in isolation or addressed them separately using multi-task frameworks, which overlooked their interconnected information flow. In this work, we propose a Collaborative transformer model for Runtime EXception detector (Co-REX), which establishes a bidirectional information flow between TLD and CEP and enables mutual enhancement through joint learning. Additionally, to evaluate the performance of Co-REX, we collect a large number of Java methods from Gitee and Github to create a benchmark dataset. Our experimental results demonstrate that Co-REX achieves 78.1% accuracy outperforming other state-of-the-art methods by a margin of at least 2.1% for TLD. It also performs better by 3.1% improvement in terms of Top-1 accuracy than others for CEP. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Java programming language

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Research on combined preprocessing algorithms for detection of center circle in circular coded target image used in art 4

Research on combined preprocessing algorithms for detection ...

引用

4th international conference on Signal Image Processing and Communication, ICSIPC 2024

作者： Wu, Qingdong Wang, Zhiqiang Xu, Yao Yan, Jun Liu, Zhaohui Shandong Luqiao Group Company Ltd. Jinan250014 China College of Transportation Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9781510682467

the corded target is an indispensable part in the study of machine vision-based measurement technology, and each coded value corresponds to a different unique value, which makes it be of an important application in image recognition. Since a center circle of the circular coded target can provide precise positioning coordinate, this paper carries out the research on the combined preprocessing algorithm for detecting the center circle of circular coded target images in order to improve the recognition efficiency and accuracy of the center circle of circular coded target image of Autonomous Rail Rapid Transit(art). Firstly, the color images captured by field experiment are gray-scale processing and smoothed by Gaussian filtering;secondly, Canny edge detection is performed on the images to accurately extract the edge features of the target images. Finally, an improved Hough transform method is used to identify the center circle contour of the extracted edges. the experimental results show that the algorithm not only improves the recognition efficiency, but also ensures the accuracy of recognition. © 2024 SPIE.

关键词： Hough transforms

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BIFROST: A Future Graph Database Runtime 40

BIFROST: A Future Graph Database Runtime

引用

40th IEEE international conference on Data engineering, ICDE 2024

作者： Clarkson, James theodorakis, Georgios Webber, Jim Neo4j London United Kingdom

ISBN: (纸本)9798350317152

BIFROST is a novel query engine for graph databases that supports high-fidelity data modeling on arbitrary and evolving graph topologies. It dynamically optimizes queries according to meta-level changes in the underlying graph (i.e. changes in topology) without the need for any explicit schema. this is possible by using state-of-the-art techniques from managed programming languages, such as self-optimizing ASTs and deoptimization, to combine query optimization and compilation. the approach provides high fidelity for even highly irregular labeled property graphs and gives good performance when compared to other systems that depend on fixed schemas for query planning and optimization. © 2024 IEEE.

关键词： Query languages

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AI Bridge Between art and science 4th

AI Bridge Between Art and Science

引用

4th international conference on Reliable Systems engineering, ICoRSE 2024

作者： Macúchová, Karolina Macúch, Jan Krblich, Jiří HiLASE Centre Institute of Physics CAS Za Radnicí 828 Dolní Břežany25241 Czech Republic Na Pankráci 420/54 Prague14000 Czech Republic

ISBN: (纸本)9783031706691

Scientific illustrations have transformed from hand-drawn sketches to sophisticated digital visualizations serving as a nexus between art and science. this paper presents integrating of AI art generation platform to create informative and engaging educational depictions of scientific phenomena. We tackle the challenge of scientific inaccuracy inherent in AI-generated artwork by implementing user-driven interventions, thereby mitigating the hit-or-miss nature of AI. through this approach, we aim to enhance the accuracy and informativeness of scientific illustrations while maintaining their captivating nature. By leveraging the capabilities of AI alongside human expertise, we seek to push the boundaries of visual representation in scientific discourse, fostering a deeper understanding and appreciation of complex phenomena. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Premixed flames

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Degradation Adaption Based Heterogeneous Face Hallucination 4

Degradation Adaption Based Heterogeneous Face Hallucination

引用

4th international conference on Big Data, artificial Intelligence and Internet of things engineering, ICBAIE 2023

作者： Teng, Zi Wang, Huan Yu, Xiaosheng Wu, Chengdong Northeastern University Faculty of Robotics Science and Engineering Shenyang110167 China

ISBN: (纸本)9798350343618

In real-world long-range surveillance systems, thermal face images captured from a distance suffer from low resolution and noise, posing challenges for thermal-to-visible face image translation. Current methods assume similar resolutions and noise-free conditions between thermal and visible images, limiting their applicability. To address these issues, we propose the Degradation Adaption Network (DANet), which synthesizes high-quality visible images from low-quality thermal images. DANet combines pretrained Generative Adversarial Network (GAN) blocks with a U-shaped deep neural network (DNN) to incorporate faithful facial priors, including geometry, facial textures, and colors. Additionally, an unsupervised degradation representation learning scheme is developed to capture abstract degradation representations of degraded thermal images in a representation space. this approach allows DANet to adapt spatial features based on the degradation representation, striking a balance between fidelity and texture faithfulness using degradation-aware feature fusion (DAFF) blocks. Experimental results demonstrate that DANet outperforms state-of-the-art methods, showing its effectiveness in handling real-world low-quality thermal images across diverse practical applications. © 2023 IEEE.

关键词： Generative adversarial networks

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Analysis of artificial Intelligence Based Human Expression 4

Analysis of Artificial Intelligence Based Human Expression

引用

4th international conference on Smart Electronics and Communication, ICOSEC 2023

作者： Nikhil, Bandaru Anitha, J. Manasa, B. Srikanth, Kolli. Kumar, K. Anil Rajeswaran, N. Birla Institute of Technology and Science-Pilani Dept. of Mechanical Engg. Hyderabad India Malla Reddy Engineering College Dept. of Cse Hyderabad India JNTU-GURAJADA Vizianagaram Dept. of It Andhra pradesh India

ISBN: (纸本)9798350300888

Facial Emotion Recognition (FER) is a current area of research in computer vision and machine learning. this study looks into how well Convolutional Neural Networks (CNNs) can identify face expressions of human emotion. CNNs have proven to perform exceptionally well in a range of computer vision applications, including image categorization, object recognition, and face recognition. To categorize the seven fundamental human emotions-anger, disgust, fear, happiness, sadness, surprise, neutral- a deep learning model is suggested utilizing CNNs. Convolutional and pooling layers are interspersed with fully connected layers for classification in the proposed model. the FER2013 dataset, which includes more than 35,000 photos, is the one utilized for training and evaluation. the performance of the proposed model was evaluated and compare it with the state-of-the-art approaches in terms of accuracy, precision, recall, and F1 score. the experimental findings show that the state-of-the-art performance in facial emotion recognition achieved by the proposed CNN-based model. © 2023 IEEE.

关键词： Emotion Recognition

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