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Adaptive Fine-Grained Feature Mining and RoI Feature Interaction Network for Small Object Detection in Aerial Images

Adaptive Fine-Grained Feature Mining and RoI Feature Interac...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Fangmin Xie Zhan Xiong Zhuoyue Wang Kun Yang Guoqiang Xiao College of Computer and Information Science Southwest University China Institute of Advanced Computer Science Leiden University Netherlands Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Object detection in drone view images remains challenging due to small-scale objects distributed non-uniformly and exhibiting weak semantic features. Additionally, external factors such as lighting conditions, viewing angles, and background clutter further complicate the detection of small objects. To address these issues, we propose a small object detector called Adaptive Fine-grained Feature Mining Network (AFMNet) based on an anchor-free framework. Firstly, an Adaptive Fine-grained Feature Mining (AFFM) module is designed to generate Regions of Interest (RoI) on high-resolution feature maps and mine fine-grained information that benefits the representation of small objects. Secondly, an Inter-RoI Feature Interaction (IRFI) block is developed to efficiently integrate complementary cues— namely, deep layer semantic information and shallow layer spatial details—and enhance RoI features. Experiments on the VisDrone dataset demonstrate that our method achieves state-of-the-art performance. The source code of our AFMNet is available at https://***/xiefangmin/AFMNet.

关键词： Adaptive systems Source coding Semantics Lighting Object detection Detectors Signal processing Feature extraction Speech processing Drones

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Zero crosstalk in anisotropic TM leaky mode with subwavelength grating metamaterials

Zero crosstalk in anisotropic TM leaky mode with subwaveleng...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Kabir, Md Faiyaz Mia, Md Borhan Ahmed, Ishtiaque Jaidye, Nafiz Ahmed, Syed Z. Kim, Sangsik Department of Electrical and Computer Engineering Texas Tech University LubbockTX79409 United States Department of Physics and Astronomy Texas Tech University LubbockTX794094 United States School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

We show that a TM leaky mode realized by subwavelength gratings (SWGs) can eliminate crosstalk between proximate waveguides. Oscillating fields i n t he SWGs allow coupling coefficient components to counteract each ot... 详细信息

ISBN: (纸本)9781957171258

关键词： Crosstalk

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Detection and Classification of Drones Through Acoustic Features Using a Spike-Based Reservoir computer for Low Power Applications 41

Detection and Classification of Drones Through Acoustic Feat...

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41st IEEE/AIAA Digital Avionics Systems Conference, DASC 2022

作者： Henderson, Alex Yakopcic, Chris Harbour, Steven Taha, Tarek M. Dayton Engineering Advanced Projects Lab Southwest Research Institute Beavercreek United States University of Dayton Department of Electrical and Computer Engineering Dayton United States

ISBN: (数字)9781665486071

ISBN: (纸本)9781665486071

Over the past few decades, the use of drones for applications such as defense, reconnaissance, agriculture, law enforcement, and others has dramatically increased. Although drones are useful for these applications, they can also be utilized to perform malicious activities, thus compromising the safety and integrity of physical infrastructures. To address this issue, various techniques have been developed to detect and identify drones, including radar, visual analysis, and radio-frequency signal processing. Furthermore, deep learning algorithms based on the recognition of acoustic drone features have been proposed to automate the detection process and overcome the current limitations in modern drone detection systems. This paper presents an auditory drone detection and identification system based on the sparse, event-driven communication nature of Spiking Neural Networks (SNNs). We investigate the use of a spiking reservoir computing model, known as a Liquid State Machine (LSM), that offers a computationally light alternative to the deep learning approaches of previous works. The LSM based auditory drone detection and identification system is demonstrated on a publicly available acoustic drone dataset, achieving an accuracy of 97.13% and 93.25% on the detection and identification tasks, respectively. To the best of our knowledge, this work presents the first spike-based implementation of an auditory drone recognition system. Moreover, this paper highlights the potential for low size, weight, and power neuromorphic hardware deployment for drone applications that may be limited to energy-constrained environments. © 2022 IEEE.

关键词： Drones

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Detecting Smart Contract Project Anomalies in Metaverse

Detecting Smart Contract Project Anomalies in Metaverse

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Su, Shen Tan, Yuntian Xue, Yue Wang, Chao Lu, Hui Tian, Zhihong Shan, Chun Du, Xiaojiang Guangzhou University Cyberspace Institute of Advanced Technoloqy Guangzhou China Guangdong Polytechnic Normal University School of Electronics and Information Guangzhou China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States

ISBN: (纸本)9798350333336

The metaverse virtual assets are carried by smart contract, thus detecting the potential smart contract vulnerabilities and malicious intension is critical to protect the metaverse digital assets and the investors' confidence. However, existing research mainly focus on the Ethereum address features, which can hardly reveal the characteristics of the entire smart contract project. In this paper, we take the first step to detect smart contract anomalies on the granularity of smart contract project, and propose a method to identify the smart contract project's subordinate addresses, and a model network which takes the runtime features of the smart contract project. We further apply our method on our dataset collected from projects deployed on Ethereum, and prove that our method could effectively recognize the similarity of smart contract projects, and identify the malicious transactions which trigger smart contract project anomalies. © 2023 IEEE.

关键词： Smart contract

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SiamCircle: Trajectory Representation Learning in Free Settings 23rd

SiamCircle: Trajectory Representation Learning in Free Sett...

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23rd International Symposium on Intelligent Data Analysis, IDA 2025

作者： Nasri, Maedeh Baratchi, Mitra Koutamanis, Alexander Rieffe, Carolien Department of Developmental Psychology Leiden University Leiden Netherlands Leiden Institute of Advanced Computer Science Leiden University Leiden Netherlands Faculty of Architecture and the Built Environment Delft University of Technology Delft Netherlands Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands Department of Psychology and Human Development Institute of Education UCL London United Kingdom

ISBN: (纸本)9783031913976

Trajectory representation learning (TRL) is an intermediate step in handling trajectory data to realize various downstream machine-learning tasks. While most previous TRL research focuses on modeling structured movements in large-scale urban spaces (e.g., cars or pedestrians on streets), this paper focuses on a more challenging scenario of modeling free movement in small-scale social spaces (e.g., children playing in a schoolyard). We present a TRL model, SiamCircle, to process raw trajectories without additional feature extraction to prevent information loss. SiamCircle adopts a Siamese network with Circle Loss to learn trajectory embeddings. Furthermore, SiamCircle employs a data augmentation process to enable self-supervised learning and enrich the input data to address the limited access to high-quality data and ground truth. We evaluate the performance of SiamCircle in downstream tasks using trajectory ranking and clustering performance via seven evaluation metrics collectively. Using an ablation study, we explored the impact of different loss functions on the model’s performance. Accordingly, we selected a 2-D convolutional design with Circle Loss as the best-performing model. In a comparative study, we compared our model against three other baselines. We observed up to 19% improvements in trajectory ranking tasks and achieved the highest average rank in supervised clustering tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Sorting

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A study of Trot Gait Control System of a Quadruped Robot Using IMU Sensor 61

A Study of Trot Gait Control System of a Quadruped Robot Usi...

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61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022

作者： Mori, Kimihiro Ohkubo, Tomoyuki Kobayashi, Kazuyuki Watanabe, Kajiro Tian, Kaiqiao Sebi, Nashwan J. Cheok, Ka C. Hosei University Graduate School of Science and Engineering Tokyo Japan Advanced Institute of Industrial Technology Tokyo Japan Oakland University School of Engineering & Computer Science Electrical & Computer Engineering Department RochesterMI United States

ISBN: (数字)9784907764784

ISBN: (纸本)9784907764784

This paper describes a stable trot gait control system for a quadruped robot that enables faster walking with stability. Compared to other gait types, it is possible to walk faster with relatively little energy expenditure, which means trot gait is suitable to control for the quadruped robot. However, trot gait does not prevent roll and pitch angle fluctuations, essentially, even when walking on flat terrain, because two legs temporarily support the robot body. Therefore, to suppress the effect of this fluctuation and stabilize the posture of the robot body, we proposed a trot gait control system using an IMU sensor and achieved faster walking without slipping. To confirm the validity of the proposed stable trot gait control system, we built a quadruped robot based on TurtleBot3 chassis and implement our system. To validate the system's effectiveness, we carried out several experiments running on various types of terrain, including sloping terrain. © 2022 The Society of Instrument and Control Engineers - SICE.

关键词： Control systems

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Interactive Agriculture relying on Artificial Intelligence and Convolution Neural Network 2

Interactive Agriculture relying on Artificial Intelligence a...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, electrical and Electronics, ICIITCEE 2024

作者： Nandhini, J. Mohanapriya, D. Kalaiarasi, G. Lakshmipriya, N. Arunprasath, M.M. Jai Shriram Engineering College Department of Electronics and Communication Engineering Tamil Nadu Tiruppur India Vignan's Foundation for Science Technology & Research Department of Advanced Computer Science and Engineering Andrapradesh Guntur India Jai Shriram Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Tiruppur India Ksr Institute for Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Tiruchengode India

ISBN: (纸本)9798350306415

Crop production is more complicated than farming, as it involves a lot of labor and very specific humid conditions in both the soil as well as the atmosphere in which to grow them. Farming has been made easier by technology, such as smart irrigation and precise plant nutrition, but these systems have a drawback: they spray water uniformly on all crops, even if some of them need little. An agricultural smart spraying system minimizes the impact on the environment while targeting chemical spray applications. In smart sprayers, which in most cases also have a targeted detection and spraying system, the targeted sensor forms the basis of precision spraying management. Despite the fact that excess water can be sprayed, it is not recommended. A crop can be protected against being affected by possible rots if moisture sensors and float sensors are used as part of the Intelligent Spraying System. Using this technology, it is possible to stop crops from being destroyed by climate change. The crop won't be harmed by pest sickness because of using Convolutional Neural Network (CNN) algorithm. This paper examines the conventional techniques for identifying plant diseases and pests. Agriculture productivity is seriously threatened by agricultural illnesses and insect pests. If pests are not found and identified quickly, they might result in considerable economic losses. So by using CNN those disease are classified in earlier stage and crops are being protected. © 2024 IEEE.

关键词： Artificial Intelligence CNN Image Processing Smart Irrigation

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Advancing Vascular Dementia Diagnosis Through Salp Swarm Optimized Convolutional Neural Network 8

Advancing Vascular Dementia Diagnosis Through Salp Swarm Opt...

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Mathkunti, Nivedita Manohara Ananthanagu, U. Abdulpur, Vidya N. Mangaiyarkarasi, D. Anitha, S. Alliance School of Advanced Computing Alliance Univerisity Department of Computer Science & Engineering Karnataka Bengaluru India Dr.D.Y Patil Pratishthan's College of Engineering Department of Electrical Engineering Maharastra Kolhapur India Institute of Science and Technology Avadi India Department of Artificial Intelligence & Machine Learning Karnataka Bengaluru562106 India

ISBN: (纸本)9798331505462

Vascular Dementia (VD) is a form of cognitive impairment seen in individuals, restricting from problems with blood vessels supplying the brain. These issues lead to strokes or reduced blood flow and gradually lead to the development of vascular dementia. Since it tends to progress slowly, diagnosis often comes after significant brain damage making prevention is crucial. Early identification of risk factors are vital to mitigate the risk of irreversible cognitive decline associated with vascular dementia. Accordingly, this research proposes an optimized neural network model for predicting vascular dementia at its earlier to improve the quality of life. The initial stage in this research involves preprocessing, where the input data is cleaned and normalized. These steps ensure that the vascular dementia dataset is cleaned of inconsistencies and prepared with normalized features for accurate analysis and modeling. Following preprocessing, relevant data features are selected using the chi-square approach, making the classification task easier. Finally, classification is performed utilizing a Convolutional Neural Network (CNN) and for fine-tuning of CNN parameters Salp Swarm Optimization (SSO) Algorithm is implemented. The execution of proposed work is processed using Python software and the outcome reveals superior performance in terms of accuracy and precision. Thereby the proposed method provides better performance with an accuracy of 94.5%, contrasted to existing methods in predicting VD. © 2024 IEEE.

关键词： Convolutional neural networks

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On-site Testing and Preventive Maintenance for a Fire Automation System Employing PSO, FA and ANN Algorithms 1

On-site Testing and Preventive Maintenance for a Fire Automa...

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1st IEEE International Conference on Emerging Research in Computational Science, ICERCS 2023

作者： Rubini, B. Kalaiarasi, G. Vasuki, S. Pradeep Kumar, S. Murugan, Suganiya Arul Stephen, C. Vels Institute of Science Technology and Advanced Studies Department of Electrical and Electronics Engineering Pallavaram Chennai India Vignan Foundation for Science Technology and Research Deemed to Be University Department of Advanced Computer Science and Engineering Andhrapradesh Guntur India M. Kumarasamy College of Engineering Department of Electronics and Communication Engineering Tamilnadu Karur India Srm Institute of Science and Technology Department of Computing Technologies Kaattankulathur Chennai India Vels Institute of Science Technology and Advanced Studies Department of Electronics and Communication Engineering Pallavaram Chennai India

ISBN: (纸本)9798350359756

engineering elements influencing in commercial and government buildings fire safety rendition buildings have been deliberated. For both new and existing buildings, all variables such as structure of building, damage due to fire from prevention compartments, Time of incidents evacuation routes should be control leverage on people's evacuation routes, controlled, and additional standard fire protection equipment are imposed. This page outlines the classes of diesel fire pumps, batteries, and pumping systems, besides the elements prompting fire rendition. Onsite diesel generator pump must be connected to a hydrant and the water pumping pressure range must be customized to 8 bar using a pressure gauge. The substantive intent of this concert is to reinforce firefighter safety. Only experienced technicians and training professionals in fire guard are responsible for this part. To simulate the battery tightness position, an extra-critical condition has been considered. Owing to the position of the fire safety properties and battery reaction in buildings, the Firefly and Particle Swarm optimization algorithms have been exerted on the iterations with objective values used for analysis in the iterative process using Matlab 2021 software. Two well-known algorithms are compared to see which provides the best results. The ANN serves as a tool for analyzing and optimizing the pump's rendition in maintaining an adequate water supply for fire emergencies. © 2023 IEEE.

关键词： Fires

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Empirical Evaluation of Internet of Things Oriented Enriched Women Protection System with Smart Sensors Association

Empirical Evaluation of Internet of Things Oriented Enriched...

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2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023

作者： Rohini, S. Deepa, A. Kalaimani, A. Rajiv Gandhi, N. Sudha, L. Pandi, V.Samuthira R.M.K Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Jeppiaar Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Panimalar Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Civil Engineering Tamil Nadu Chennai India S.A Engineering College Department of Computer Sciece and Engineering Tamil Nadu Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350303452

As a result of modernity and advances in technology, protecting women has emerged as an issue that has to be addressed immediately not just in India but also in a number of other countries. Due to the structural difficulties that are connected with handling cases of this nature, the police are unable to respond to valid calls for assistance. It is difficult to approach the murder scene in an individual manner, and it is hard to determine where the crime began and where the victims died. It is also difficult to determine who committed the crime. As a direct consequence of this, the proportion of crimes in India that are perpetrated against women and children continues to climb, sowing the seed of dread in the minds of the people who live in the nation. As a direct consequence of this, the government has enacted a multitude of regulations with the intention of safeguarding the well-being of women and children. If a female volunteer in this research feels uncomfortable or unsafe in any way, she is told to use the 'Panic Button'. All these communications are handled by using the latest technology called Internet of Things (IoT) and when the alarm is activated, the gadget makes use of technology known as the Global Positioning System (GPS) to determine the exact position of the user. It then sends a signal of distress through GSM to the user's phone as well as the closest police station. A module connected to the Internet of Things is used to perform continuous monitoring of the location, and the website is automatically updated to reflect any changes. The buzzer will go off as soon as the accelerometer detects that she has fallen, therefore alerting anybody in the vicinity to the fact that she requires assistance. The key advantage of this research is the development of a portable safety device that can be used to safeguard women no matter where they go. © 2023 IEEE.

关键词： Global positioning system

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