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Event extraction enhanced by fusing trigger feature 3

Event extraction enhanced by fusing trigger feature

引用

3rd international conference on computer vision and Data Mining, ICCVDM 2022

作者： Li, Xingyu Wang, Licai Huang, Yangchen Luo, Qibin Du, Tianfeng North China Institute of Computing Technology Smart Plat Rd Department Beijing100083 China School of Mangement and Engineering Capital University of Economics and Business Beijing100070 China

ISBN: (纸本)9781510661363

Event extraction is a key research direction in the field of information extraction. In order to improve the effect of event extraction and solve the problem that the general event extraction method cannot make full use of the text feature information, an event extraction method integrating trigger word features is proposed. By building a remote trigger thesaurus, we can provide additional feature information for the event type classification model, enhance the ability of discovering event trigger words. Then the event arguments extraction model integrates the event type and trigger distance features to improve the representation learning ability. Finally, connecting the event type classification model and the event arguments extraction model in series to complete event extraction. Experiments are carried out on the DuEE dataset and the result shows that our model has more outstanding performance than other models. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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Improved Drone Image Small Target Detection Based on YOLOv7 3

Improved Drone Image Small Target Detection Based on YOLOv7

引用

3rd international conference on Optics and Machine vision, ICOMV 2024

作者： Zhang, Hui Wan, Fang Lei, Guangbo Xu, Li School of Computer Science Hubei University of Technology Wuhan430068 China

ISBN: (纸本)9781510680319

With the development of artificial intelligence, the use of drones in everyday life is becoming more and more popular, but there is still room for improvement in terms of detection accuracy and detection speed when using drones to capture aerial images for small target detection. This paper proposes a target detection and recognition method based on an improved YOLOv7 for small target detection applied to UAV aerial photography. First, the backbone network of MobileOne is improved, and the MobileOne module is added to the YOLOv7 model, which replaces some of the standard convolutional layers in the YOLOv7 backbone network, effectively speeding up the inference speed and reducing the number of model parameters;secondly, based on the ConvNeXt structure, the CNeB module is constructed to improve the feature extraction capability of the YOLOv7 network and target detection;finally, the Wise-IoU loss function is introduced to reduce the competitiveness of high-quality anchor frames while minimizing the harmful gradients generated by low-quality examples. Our improved method is compared with traditional target detection algorithms such as YOLOv7 on the VisDrone2019 dataset. The results show that the improved method has better detection results. © 2024 SPIE.

关键词： Drones

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Indian Sign Language Recognition in Real Time using YOLO NAS 3

Indian Sign Language Recognition in Real Time using YOLO NAS

引用

3rd international conference for Advancement in Technology, ICONAT 2024

作者： Raj, Rohit Sreemathy, R. Turuk, Mousami Jagdale, Jayashree Anish, Mohammad Pune Institute of Computer Technology Department of E&TC Engineering Pune India Pune Institute of Computer Technology Department of Information Technology Pune India

ISBN: (纸本)9798350354171

Normal people typically communicate using voice, while deaf individuals use sign language to communicate with each other. However, a challenge arises when deaf people need to interact with those who do not understand sign language. To address this issue, we propose developing a model that can recognize Indian Sign Language and translate it into text. Deep learning approaches have been used into computer vision in recent years, greatly advancing the area of sign language identification and improving accessibility for the deaf. To achieve real-time recognition of Indian Sign Language, we have used YOLO NAS (You Only Look Once Neural Architecture Search) object detection *** YOLO NAS architecture achieves 0.9568 mean Average Precision (mAP) with intersection over union (IoU) threshold of 50% across 100 classes, using our selfcreated Sign Language dataset. © 2024 IEEE.

关键词： Object detection

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A Sustainable approach to Design and Optimize a Solar Powered E2W Charging Station for Manipal University Jaipur 3

A Sustainable approach to Design and Optimize a Solar Powere...

引用

3rd IEEE international conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Kiran Chaurasia, Sandeep Ravishankar Kamath, H. Manipal University Jaipur Department of Electrical Engineering Jaipur India Manipal University Jaipur Department of Computer Science & Engineering Jaipur India The Assam Kaziranga University Department of Electrical Engineering Jorhat India

ISBN: (纸本)9798350387193

India witnessed 34.42 % growth of electric two-wheelers (E2W) in the third quarter of fiscal year 2024. The average solar incidence across the country ranges between 4 - 7 kWh/sq.m/day. Adoption of electric vehicles could foster India's commitment towards sustainability. Rajasthan receives the highest annual radiation energy. The state also has highest numbers of universities. Setting up a E2W charging station on the university campus will increase charging convenience, support research activities and reduce the carbon footprint. This case study constructs a self-financed 18.00kWp E2W charging station using PV Syst V7.4.3 software. The Ideal scenario projected a payback period of 6.2 years with 15620.00 USD capital investment. The levelized cost of energy (LCOE) of the E2W station is 0.05 USD which is less than the charging rate of public electric vehicle charging station across the state. © 2024 IEEE.

关键词： Charging stations

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A study of a federated learning framework based on the interstellar file system and blockchain: Private Blockchain Federated Learning 3

A study of a federated learning framework based on the inter...

引用

3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Zhang, Peng Liu, Gang Chen, Zhiyu Guo, Jianwei Liu, Peng University of Technology School of Computer Science and Engineering Changchun ChangChun China Jilin Heshun Hengtong Technology Co. Product Department ChangChun China

ISBN: (纸本)9781665459112

Federated learning is a scalable machine learning paradigm in which a large group of individuals collaborates to build a high-quality machine learning model. This paper proposes Private Blockchain Federated Learning (PriChainFL). It is a federated learning method that combines blockchain and IPFS, in response to the fact that federated learning is still vulnerable to attacks such as data poisoning and member inference attacks. It also reduces the storage cost of blockchain. © 2022 IEEE.

关键词： Blockchain

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Intelligent English Automatic Translation System Based on TTS Technology 3

Intelligent English Automatic Translation System Based on TT...

引用

3rd international conference on Artificial Intelligence and Autonomous Robot Systems, AIARS 2024

作者： Sun, Xiyang Wang, Zhuo School of Foreign Languages Dalian University of Science and Technology Liaoning Dalian China

ISBN: (纸本)9798350376173

The intelligent English automatic translation system was built based on TTS technology. In the development process of the system, careful selection and configuration of text to speech converters and speech processors were carried out, and TTS technology was cleverly integrated, fully covering key aspects such as text analysis, prosody control, and speech synthesis. In order to better meet the specific requirements of English translation, the system has specially designed several key components, including but not limited to automatic segmentation and annotation of continuous speech, pre prosodic control of speech, speech synthesis, and optimization and reduction of speech databases. These carefully designed hardware units and software modules were integrated with each other, enabling the intelligent English automatic translation system to operate efficiently and smoothly. Through experiments, it can be seen that the intelligent English automatic translation system based on TTS technology performed well in terms of accuracy, ranging from 86.11% to 95.27%, which was significantly better than ordinary intelligent translation systems and traditional translation systems. This result fully proved that this system had a relatively high level of accuracy in processing English speech translation. The comprehensive design of the system has not only improved translation quality, but also laid the foundation for the development of future intelligent translation technology. © 2024 IEEE.

关键词： computer aided language translation

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Design of Battery Powered Electric Vehicle for Sustainable Mobility with Environmental Impact using Intelligent control and Autonomous Systems 3

Design of Battery Powered Electric Vehicle for Sustainable M...

引用

3rd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Sujitha, S. Vinoth Kumar, K. Devadiga, Dheeresh Vijay Dixen, Dayas A Harshita, K. Dony Snehit, P. New Horizon College of Engineering Department of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798350375190

The need for environmental protection and energy conservation in the twenty-first century has highlighted the urgency of advancing Electric Vehicle (EV) technology. This research study contributes to this trajectory by introducing a novel foot-controlled steering system for electric skateboards, aiming to enhance vehicle control while promoting sustainable transportation practices. This study proposes the conceptualization and design of the electric skateboard utilizing computer-Aided Design (CAD) tools, followed by the development of simulation models to validate its performance across diverse road conditions. Comprehensive equipment and cost analysis are then conducted to assess the feasibility and economic viability of the proposed model. Furthermore, the research study includes the manufacturing process, encompassing the assembly of skateboards, integration of electric motor drives, and the design of in-built controllers to facilitate seamless operation. Notably, this study focuses on refining the design to optimize performance for off-road usage, thereby expanding the utility and versatility of the electric skateboard. By integrating innovative engineering solutions with sustainability principles, this study not only contributes to the advancement of electric vehicle technology but also advances the realization of efficient and intelligent transportation systems, aligning with the requirements of contemporary environmental stewardship and economic development. © 2024 IEEE.

关键词： Automotive industry

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An experimental teaching platform for machine vision-based real-time detection taking quality inspection of paper cups as instance 3

An experimental teaching platform for machine vision-based r...

引用

3rd international conference on Educational Technology, ICET 2023

作者： Huang, Yanzhe Luo, Yabo Zhou, Xiangyu Wuhan University of Technology School of Mechanical and Electronic Engineering Wuhan China

ISBN: (纸本)9798350302332

In order to improve the quality of students' practical training, a real-time detection system experimental platform based on machine vision has been designed. The system has functions of real-time sampling, detection, defective product removal, result display and data storage, and its structure covers three parts: hardware platform, detection algorithm, and software function implementation. The hardware platform includes image acquisition module, material transportation module and defective product removal module, and the control circuit is based on the development of Arduino and STM32. The detection algorithm is developed based on OPENCV, and it is designed to detect three types of defects: cup rim concavity, cracking, and out-of-roundness. The software system is jointly developed using Visual Studio 2019 and Qt Creator 4.9.1, and it has good interactivity. With this experimental platform, teaching work such as image acquisition system construction, dynamic sampling problem analysis, image detection algorithm development, and interactive interface implementation can be carried out, so as to improve students' engineering design ability in many aspects. © 2023 IEEE.

关键词： computer vision

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Enhancing Device Authentication in IoT Security Application using Artificial Intelligence: A Survey 3

Enhancing Device Authentication in IoT Security Application ...

引用

3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Brogya, Maame Serwah Dumfeh Ayuso, Enrique Shukla, Aasheesh Goyal, Amit Kumar Sain, Mangal Dongseo University Dept. of Computer Engineering Busan Korea Republic of Gla University Department of Electronics and Communication Mathura India Chandigarh University Department of Computer Science and Engineering Mohali140413 India

ISBN: (纸本)9798331528201

Technological advancement over the last decade has seen significant technological development, particularly in IoT, which is the most used and commercialized. This is due to its convenience, as it gives users remote control of their appliances via portable devices like smartphones and tablets, without needing to be physically present or close to those devices. As IoT technologies continue to grow and new innovative solutions for everyday applications are being developed there are more interconnected devices and large volumes of data being generated every second. However, the rapid growth of IoT has heightened security concerns, especially around device authentication. This paper reviews IoT authentication complexities and explores Machine Learning solutions under AI, comparing various algorithms and, providing a foundation for researchers and developers in the field. © 2024 IEEE.

关键词： Adversarial machine learning

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Attention fusion sentiment analysis with cross-modal sentiment augmentation 3

Attention fusion sentiment analysis with cross-modal sentime...

引用

3rd international conference on Machine vision, Automatic Identification, and Detection, MVAID 2024

作者： Wang, Xuyang Shi, Haojun School of Computer and Communication Lanzhou University of Technology Lanzhou730000 China

ISBN: (纸本)9781510681880

Multimodal sentiment analysis is a method that combines multiple modal information such as text, image and audio to analyze and understand people's emotional states and emotional expressions. This method can capture the sentiment more comprehensively and improve the accuracy and effect of sentiment analysis. However, most of the previous studies focus on the fusion mode between modalities, ignoring the emotional features beyond the text information, and fail to fully mine the semantic emotional information contained in it. To solve the above problems, an Attention Fusion Network with Cross-modal Emotion Enhancement (AFNCEE) is proposed. Firstly, Long Short-Term Memory (LSTM) was used to obtain contextual semantic information from a single modality, and the cross-modal Transformer stacked structure was used to fuse text, audio and visual modal features to enhance the hierarchical depth of fusion. Then, the SenticNet knowledge base is used to construct a text sentiment knowledge graph to enhance its additional representation. Finally, a feature-based attention fusion module is designed to dynamically adjust the additional representation and the weight of each modal representation, so as to realize multi-modal fusion. © 2024 SPIE.

关键词： Knowledge graph

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