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共 47854 条记录，以下是1171-1180 订阅

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Collaborative Platform for Content Creators and Brands Based on Semantic Search 2

Collaborative Platform for Content Creators and Brands Based...

引用

2nd international conference on advances in Computation, Communication and Information technology, ICAICCIT 2024

作者： Magrey, Basit Shafiq Ramneet Chauhan, Ayushi Singh, Sarthak Department of Computer Science and Engineering Sharda School of Engineering and Technology Sharda University UP Greater Noida India

ISBN: (纸本)9798331541217

In today's changing world establishing strong connections, between sponsors and content creators is key to successful brand promotion. This paper presents a platform designed to enhance connections by utilizing matching methods to help sponsors identify and engage with streamers who align with their brand values and audience demographics effectively boosting the impact of sponsorships. Semantic matching involves evaluating the significance of search inquiries and content to enhance the precision and suitability of these associations. This research investigates the use of matching to improve search capabilities, on the platform. It also examines how this affects the connection, between sponsors and creators while highlighting the benefits and obstacles of this approach. © 2024 IEEE.

关键词： Latent semantic analysis

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Empowering IoT Security by Classifying Threat Detection Through Machine Learning

Empowering IoT Security by Classifying Threat Detection Thro...

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Balavaseekaran, I. Dileep, Ambili Sabitha, Sai Hindustan Institute Of Technology And Science Dept Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

Daily lives have been made much easier with the invasion of IoT devices in many fields such as health care, education, smart homes, agriculture, etc. Nowadays these devices are prone to many cyber attacks that exist currently and require impregnable security. The most common attacks that happen on an IoT device are DoS and DDoS. The methodology considered in this research employs machine learning algorithms and PCA (Principal Component Analysis) to classify the type of DDoS and DoS attacks that occur on IoT devices. The research also includes the implementation of genetic algorithm in evolutionary feature selection to optimize the features used in the classification process. This research work employs six supervised machine-learning algorithms such as K-Nearest Neighbor (KNN), Decision Tree, Naive Bayes, Neural Network, Random Forest, and Boosted Tree, to classify the different types of attacks that may occur in the Internet of Things (IoT) devices and a comparative analysis on these algorithms are performed. © 2024 IEEE.

关键词： Internet of things

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Single Image Super-Resolution Reconstruction Based on Multi-Scale Attention Mechanism 16

Single Image Super-Resolution Reconstruction Based on Multi-...

引用

2024 16th international conference on Graphics and Image Processing, ICGIP 2024

作者： Su, Jin-Sheng Zhang, Ming-Jun Yu, Wen-Jing Dept. of Network Technology Software Engineering Institute of Guangzhou 510990 China

ISBN: (数字)9781510688780

ISBN: (纸本)9781510688773

This study is dedicated to solving the problem of single-image super-resolution reconstruction, particularly by introducing a multi-scale attention mechanism to enhance the reconstruction effectiveness. advances in super-resolution technology have provided unprecedented possibilities for reconstructing images with low clarity, yet challenges regarding reconstruction quality and efficiency remain. Based on a review of the literature concerning attention mechanisms and their applications in super-resolution, this paper proposes a new network architecture that incorporates a carefully designed multi-scale attention module. The research demonstrates through experiments that the new algorithm can effectively capture the feature information of images and achieve improvements in detail recovery. Both quantitative and qualitative experimental results indicate that the proposed method outperforms existing approaches in the task of super-resolving images, showcasing significant advantages and practical application value. The paper also provides a detailed analysis of key modules within the algorithm and discusses the results obtained. Overall, this research successfully opens up new avenues for enhancing image reconstruction performance and offers valuable insights for future work. © 2025 SPIE.

关键词： Image reconstruction

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Novel Regularization Method Exploiting Mutual Information for Deep Neural Networks 2

Novel Regularization Method Exploiting Mutual Information fo...

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2nd international conference on robotics, Artificial Intelligence and Intelligent Control, RAIIC 2023

作者： Song, Zichen Chen, Ziyang Xia, Shengjie Lanzhou University School of Information Science & Engineering Lanzhou China Dalian University of Technology International School of Information Science & Engineering Dalian China

ISBN: (纸本)9798350328004

Dropout is a powerful way for preventing model overfitting. However, it is inefficient due to it randomly ignoring some neurons. Although there are many ways on Dropout, they are still either inefficient on improving generalization ability or not effective enough. In this paper, we propose Mutual Information Dropout, which is an efficient Dropout based on dropping neurons with low mutual information. In Mutual Information Dropout, instead of randomly ignoring some neurons, we first evaluated the mutual information of neurons to dropout with mutual information below a certain threshold. In this way, Mutual Information Dropout can achieve effective improving generalization ability with evaluate neurons. Extensive experiments on Three datasets show that Mutual Information Dropout is much more efficient than many existing Dropout and can meanwhile achieve comparable or even better generalization ability. © 2023 IEEE.

关键词： Neurons

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Low-Cost Speech to Text Translation Handwriting Robot using Arduino and Google API 14

Low-Cost Speech to Text Translation Handwriting Robot using ...

引用

14th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Ramya, M.V. Tippannavar, Sanjay S. Department of Robotics and Automation JSS Academy of Technical Education Bengaluru India Department of Electronics and Communication Engineering JSS Science and Technological University Mysuru India

Among all forms of communication, writing is the most popular and universally recognised. Writing proficiency is thus crucial for reaching professional and corporate objectives. Unfortunately, it could be difficult in unique situations involving persons with varied abilities. The solution is to carry out the writing job utilising a robotic arm (SCARA). Writing an alphabet in both English and a regional language will be made possible by automation. The hardware and software requirements for building a robot that can do a task that is typically completed by a portable pen are covered in this paper. © Grenze Scientific Society, 2023.

关键词： Speech recognition

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'Precision Agriculture Farming' Enhancing Farming Efficiency through technology Integration 1

'Precision Agriculture Farming' Enhancing Farming Efficiency...

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1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Sharma, Prashant Kumar, Pratyaksh Singh, Praveen Kumar Rana, Arun Kumar Galgotias College of Engineering And Technology Dept. Of Computer Science And Engineering Greater Noida India

ISBN: (纸本)9798350356816

Precision agriculture, or precision farming, or smart farming, refers to a contemporary approach that combines technology and data analytics with agricultural practices. This research paper examines the concept of precision agriculture, its principles, advantages, disadvantages, and potential to transform farming practices. Through the use of various technologies including GPS, sensors, drones, and data analytics, precision agriculture seeks to maximize resource efficiency, enhance crop yields, reduce the environmental footprint, and boost overall profitability for the farm. The paper also addresses case studies and real-life implementations of precision agriculture and illustrates its effectiveness in various sectors of agriculture. It further identifies the challenges and constraints of adopting precision agriculture and proposes possible solutions to overcome these challenges. This paper generally offers insight into the revolutionary potential of precision agriculture in reshaping the future of farming. © 2024 IEEE.

关键词： Smart agriculture

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Semantic Intrinsic and Extrinsic LiDAR-Camera Calibration in Targetless On-Orbit Environments 3

Semantic Intrinsic and Extrinsic LiDAR-Camera Calibration in...

引用

3rd international conference on Service robotics, ICoSR 2024

作者： Zhang, Qianyu Zhang, Shengyang Zhao, Yutao Zuo, Jianhong Wu, Aodi Wan, Xue Shu, Leizheng Feng, Xuan University of Chinese Academy of Sciences Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Nanjing University of Aeronautics and Astronautics Beijing China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350367119

With the increasing complexity of on-orbit service tasks, there is a growing demand for multi-modal sensing capabilities. LiDAR and camera are the primary sensors for space service robotics, their data fusion can enhance perceptual understanding. However, the intrinsic and extrinsic parameters of LiDAR and camera may be affected by temperature and vibration during launch. How to re-calibrate the intrinsic and extrinsic parameters in a targetless on-orbit environment remains an open problem. In this paper, we propose a coarse-to-fine intrinsic and extrinsic calibration method that utilizes line and plane semantic features extracted from satellite panels in sequential data to achieve joint calibration. Initially, we optimize the intrinsic and extrinsic parameters roughly based on reprojection errors derived from line features. Subsequently, fine optimization is performed using plane constraints obtained from SfM point cloud aligned with LiDAR point cloud in each frame, along with 3D-2D line feature matching between LiDAR registration point cloud and image in each frame. The method was validated on a simulated dataset consisting of satellite fly-around image and point cloud sequences within the range of 10 to 20 meters. The results show that the average rotation error is 0.24°, the average translation error is 0.02 m, and the average intrinsic error is 1.33 pixels, which proves the accuracy and robustness of the proposed method. © 2024 IEEE.

关键词： Sensor data fusion

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A Convenient Calibration Method for Robot Hand Eye System Without External Calibration Objects

A Convenient Calibration Method for Robot Hand Eye System Wi...

引用

2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Zhou, Wei Ji, Yuan Zhang, Juntai Ma, Cui Yang, Fan He, Kai Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Key Laboratory of Precision Engineering Shenzhen518055 China

ISBN: (纸本)9781665481090

For the hand eye system calibration problem of inspection robot equipped with dual robotic arms and RGB-D camera, a simplified joint calibration method based on deep learning is proposed. It eliminates the need for external systems and calibration boards, resolving the calibration of the dual robotic arms and the extrinsic calibration of the RGB-D camera within the hand eye system of the inspection robot. By utilizing nonlinear optimization, it effectively reduces measurement noise and minimizes the propagation and influence of calibration errors in the coordinate transformation. Experimental results demonstrate that the proposed method achieves an average calibration error of 0.5mm for the dual robotic arms, and a minimum calibration error of 1.2mm for the camera's extrinsic parameters. Consequently, it significantly enhances the hand eye localization accuracy of the inspection robot during task execution. The innovative approach holds promising potential for improving the practical application of inspection robots. © 2024 IEEE.

关键词： Robotic arms

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Research on Lightweight Fire Detection Algorithm Based on YOLOv5s 7

Research on Lightweight Fire Detection Algorithm Based on YO...

引用

7th international conference on Intelligent robotics and Control engineering, IRCE 2024

作者： Tang, Wei Zhang, He Hou, YuJie Duan, AoBo Liu, YingWei Zhou, GuoQing Li, Qian Zheng, XiaoHu Shaanxi University of Science & Technology College of Electrical and Control Engineering Xi'an China

ISBN: (纸本)9798350352399

Aiming at the problems of complex structure and heavy calculation of existing fire detection algorithms, a lightweight fire detection algorithm based on YOLOv5s is proposed in this paper. Considering the characteristics of rapid fire spread, the algorithm specifically optimizes the Backbone and Neck structure of YOLOv5s network to achieve rapid and accurate identification of initial flame and smoke. The basic idea of the algorithm is as follows: Firstly, the Conv module and C3 structure in C3darknet53, the backbone network of YOLOv5s, are replaced with GhostConv and C3Ghost respectively, and auxiliary feature maps are introduced to expand the receptor field of the backbone network and improve the detection efficiency;Secondly, Gsconv convolution is used to replace the conventional convolution operation, which can reduce the number of parameters and computation of the neck network while maintaining the semantic information connection of the channel. The experimental results show that the proposed algorithm reduces the number of parameters by 44.4% and the amount of computation by 53.2%, while maintaining the stability of its performance, which makes the algorithm suitable for resource-constrained environment and can detect flame smoke quickly and accurately. © 2024 IEEE.

关键词： Convolution

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Early Fault Detection in Rolling Element Bearings Using Signal Processing Techniques 21

Early Fault Detection in Rolling Element Bearings Using Sign...

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21st IEEE international conference on Smart Communities: Improving Quality of Life using AI, robotics and IoT, HONET 2024

作者： Saeed, Ali Akram, M. Usman Khan, Muazzam A. Afsar, M. Belal Quaid-i-Azam University ICESCO Big Data Analytics and Edge Computing Department of Computer Science Islamabad Pakistan National University of Sciences and Technology Department of Computer and Software Engineering Islamabad Pakistan Otto-von-Guericke University Faculty of Electrical Engineering and Information Technology Maddeburg Germany

ISBN: (纸本)9798350378078

Many studies show that bearings are the most vulnerable components in low-voltage motors. While advanced bearing diagnostic systems exist, their cost can be a barrier for non-critical machinery due to the potential wait time to see a return on investment. This research explores the feasibility of using basic signal processing techniques on vibration data for bearing condition monitoring. The primary goal is to analyze benchmark data from the Case Western Reserve University (CWRU) dataset and establish a baseline performance for this data-driven approach. The results suggest that, with appropriate signal processing, it's possible to achieve early detection of bearing faults, leading to more efficient time-To-fault identification with higher detection accuracies ranging from 83 % to 100 % for each method. © 2024 IEEE.

关键词： Signal modulation

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