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共 5812 条记录，以下是101-110 订阅

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Fusion of computer Vision and Natural Language processing: Automated Image Caption Generation 4

Fusion of Computer Vision and Natural Language Processing: A...

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4th international conference on intelligent Technologies, CONIT 2024

作者： Akku, Chandra Prakash Cheemalwar, Srushith Chamakura, Vasanth Gogu, Shiva Shankar Swaraja, K. Arun Vignesh, N. Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Electronics and Communication Engineering Hyderabad India

ISBN: (纸本)9798350349900

In this work the advancement in the field of natural language processing and computer vision, introduces a robust image captioning model that harnesses the capabilities of attention mechanisms. the model encompasses several core components, including the loading and preprocessing of datasets and the integration of MobileNetV3small. the model architecture is designed with a multi-layer transformer decoder, indicating self-attention, and cross-attention mechanisms for a deeper understanding of the image and text data. Training this model involves fine-tuning MobileNetV3small and optimizing the transformer-based decoder for accurate and context-aware caption generation. the utilization of MobileNetV3small and the Transformer-based decoder marks a significant advancement in image captioning, and the model holds promise for applications in automated image description and content generation. the model was tested on diverse datasets, as exemplified by its performance on both the Flicker8k and Conceptual Captions datasets. the training process involves a comprehensive pipeline, encompassing dataset preparation, image feature extraction, and tokenization, ensuring a holistic approach to model learning. the comprehensive result analysis highlighted the enhanced captioning results of the proposed method with CIDEr values of 37.20 and 25.40 on the Flickr8k dataset and conceptual captions dataset. © 2024 ieee.

关键词： Decoding

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Personalized Dietary Recommendations for Health and Disease Prevention 4

Personalized Dietary Recommendations for Health and Disease ...

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4th ieee international conference on Applied Electromagnetics, Signal processing, and communication, AESPC 2024

作者： Ahmad, Md. Irshad Priyadarshini Behera, Mandakini Singh, Kanan Tiwary, Komal Rupsa, Potnuru Darshana, Subhashree School of Computer Engineering KIIT-DU Bhubaneswar India

ISBN: (纸本)9798331528171

A dangerous lifestyle serves as one of the important purposes for numerous health troubles and positive diseases. this undertaking investigates the importance of personalized weight loss plan tips for selling health and well-being. It emphasizes the link between nutritional alternatives and chronic illnesses like cardiovascular sickness, diabetes, and certain cancers. the paintings highlight the need for people to recall elements such as age and nutrition requirements when making dietary decisions. this machine addresses the challenge of low compliance with modern dietary guidelines through presenting customers with tailored recommendation that aligns with their options and restrictions. the project additionally explores the relationship between eating regimens and precise health conditions. this mission offers the person dietary health worries and necessities. © 2024 ieee.

关键词： Disease control

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Privacy-preserving kNN Classification Query Scheme for Encrypted Data in Outsourced Environments for Smart Grid 4

Privacy-preserving kNN Classification Query Scheme for Encry...

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4th international conference on computer communication and Artificial Intelligence (CCAI)

作者： Wang, Haolin Zhao, Yun Cai, Ziwen Zhao, Hao CSG Elect Power Res Inst Guangzhou Peoples R China Guangdong Prov Key Lab Intelligent Measurement & Guangzhou Peoples R China Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu Peoples R China

ISBN: (纸本)9798350362770;9798350362763

With the increasing application of cloud computing in the power system, numerous power companies outsource their data to cloud service providers to reduce data management costs. However, there are many privacy issues. Privacy-preserving kNN classification queries for power data stand out as a typical application of privacy computing technology in smart grid environments. Nevertheless, numerous kNN classification query solutions still face challenges such as security vulnerabilities, inapplicability to data outsourcing scenarios, and low computational efficiency. To address these issues, we introduced the SKL, SKS, and SCF protocols, laying the foundation for a privacy-preserving kNN classification query scheme for encrypted data in outsourced environments for the smart grid. Furthermore, we proved the security of our scheme under the semi-honest security model. Lastly, empirical validation attests to the high computational efficiency of our proposed scheme.

关键词： smart grid IoT privacy-preserving kNN data outsourcing

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TizenRT OS Based Data Compression Algorithms for IoT Devices 4

TizenRT OS Based Data Compression Algorithms for IoT Devices

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4th ieee international conference on Computing, communication, and intelligent Systems, ICCCIS 2023

作者： Chamak, Tanmoy Roy Kaushik, Sachi Singhal, Shiven Dadheech, Aditya Anitha, Prof. A. Jenicka, Prof. S. thapa, Vidisha School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Samsung Research Institute Karnataka Bangalore India

ISBN: (纸本)9798350306118

the paper investigates the integration and adaptation of the LZ4 compression algorithm within the context of TizenRT, in addition to existing algorithms Miniz and LZMA. TizenRT, a real-Time operating system tailored for Internet of things (IoT) devices, presents unique challenges in balancing compression efficiency and resource constraints. the study evaluates the performance of LZ4 alongside Miniz and LZMA in terms of compression ratios, processing overhead, and memory utilization. Experimental results demonstrate the feasibility of LZ4's adoption in TizenRT, highlighting its potential to enhance data compression and decompression operations while adhering to the stringent requirements of IoT devices. the findings contribute to the optimization of data management strategies within the TizenRT ecosystem. © 2023 ieee.

关键词： Internet of things

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A Confusion-Enhanced Deep Learning Model for Knowledge Tracing 4

A Confusion-Enhanced Deep Learning Model for Knowledge Traci...

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4th international conference on computer communication and Artificial Intelligence (CCAI)

作者： Yin, Ming Huang, Ruihe Northwestern Polytech Univ Sch Software Xian Peoples R China

ISBN: (纸本)9798350362770;9798350362763

Knowledge tracing (KT) refers to the task of tracing the changing knowledge state of learners and predicting their future performance through their learning records. It is the core of computer assisted adaptive cognitive learning. Existing KT research uses deep learning methods to explore the relationship between concepts and problems, which improves prediction performance. However, few models apply educational psychology theories. Guiding students to learn through educational psychology theories is also important in the process of learning, which is an important basis for distinguishing different students' knowledge state. To solve this problem, we propose a gated network with confusion analysis mechanism (CDKT) to predict the confusion level of learners and trace the knowledge state of learners during learning based on educational psychology theory. the proposed model can model the knowledge state of students through three gated network to adapt to the individual development of learners and individual differences after training. It can also predict students' performance in new exercise.

关键词： gated network knowledge tracing deep learning intelligent education

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Real-Time Object Detection Methods for Road Scenarios 20

Real-Time Object Detection Methods for Road Scenarios

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20th ieee international conference on intelligent computer communication and processing conference, ICCP 2024

作者： Chete, Doru Negru, Mihai Mocanu, Adrian Robert Bosch Srl Cluj-Napoca Romania Technical University of Cluj-Napoca Department of Computer Science Cluj-Napoca Romania

ISBN: (纸本)9798331539979

Wildlife on public roads presents a public safety problem as well as an environmental concern. the field of object detection within computer Vision offers some approaches that can be used either in autonomous vehicles or within emergency braking systems for collision avoidance. this paper aims to study how a popular and efficient object detection model and a keypoint-based model compare against each other on an SoC specialized for computer Vision tasks which is used in automotive systems. Insights into how these object detection models perform on resource-constrained hardware and into the importance of the overall approach are gained while also highlighting the advantages and disadvantages of each method and the hindrances of deploying such algorithms on hardware. While well-established models like YOLO outpace the implemented keypoint-based approach in both precision and speed, the total runtime of the two models is ultimately close, with the biggest takeaway being that the robust YOLO model also requires extensive post-processing, which is computationally expensive, especially on an embedded SoC. © 2024 ieee.

关键词： Highway accidents

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Tropical Cyclone Intensity Prediction Using Deep Learning Techniques- A Survey 4

Tropical Cyclone Intensity Prediction Using Deep Learning Te...

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4th ieee international conference on Applied Electromagnetics, Signal processing, and communication, AESPC 2024

作者： Ilayaraja, V. Rajamohana, S.P. Jagadeesan, S. Aishwarya, V. Rakesh, M. School of Computer Science and Engineering Vellore Institute of Technology Tamilnadu Vellore632 014 India School of Engineering & Technology Pondicherry University Department of Computer Science Puducherry Karaikal India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Department of Software and Systems Engineering Tamil Nadu Vellore632 014 India

ISBN: (纸本)9798331528171

Tropical cyclones, characterized by strong winds and heavy rainfall, threaten human life in coastal regions crucial to the economy, including fisheries, agriculture, tourism, and infrastructure. their frequent occurrence impacts communities reliant on these industries for livelihoods. Accurate estimation of tropical cyclone intensity is vital for disaster preparedness, risk assessment, and timely evacuations. Recent advancements in machine learning and deep learning have been applied to predict cyclone intensity from satellite images, providing insights into cyclone dynamics and enhancing disaster response. this paper analyzes recent research on intensity estimation using various machine learning algorithms and discusses future prospects for improving accuracy and reliability. © 2024 ieee.

关键词： Tropical cyclone

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Research and Protection of Security Technology for intelligent Connected Vehicle Keys 4

Research and Protection of Security Technology for Intellige...

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4th international conference on Electronic Information Engineering and computer Science, EIECS 2024

作者： Yu, Qi Guo, Zhen Zhi, Qianchuang Liu, Tianling Ren, Shixuan Sun, Dongqing Catarc Intelligent and Connected Technology Co. LTd. China Automotive Technology & Research Center Co. Ltd. Tianjin China

ISBN: (纸本)9798331531409

With the progress of technology and the popularity of intelligent vehicles, traditional physical keys are gradually being replaced by smart keys and remote keys. Smart keys communicate with the vehicle through radio signals or near field communication technology, enabling the owner to remotely unlock the vehicle, start the engine, and perform other convenient functions. However, there are concerns about their safety. Studies have shown that smart keys and digital keys have the potential risk of being hacked or cracked, which may allow unauthorized personnel to access and operate the vehicle, thus threatening the safety of both the owner and the vehicle. therefore, to ensure the security of the key system in intelligent connected vehicles, it is necessary to conduct in-depth research and discussion on current technology, existing security risks, and corresponding protection schemes. the purpose of this paper is to discuss the importance of key security in intelligent and connected vehicles, analyze current vehicle unlocking technologies and their associated attack methods, conduct experimental verification, and propose protection schemes for commonly used attack methods, discuss the future trends in key security to ensure the security of these systems. © 2024 ieee.

关键词： attack and defense digital key intelligent connected vehicle smart key

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Research on Task Offloading Strategies in Edge Computing Environments 4

Research on Task Offloading Strategies in Edge Computing Env...

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4th international conference on Electronic Information Engineering and computer communication, EIECC 2024

作者： Liu, Dan Sun, Yuting Chi, Yongjie Changchun University of Science and Technology College of Computer Science and Technology Jilin Changchun China

ISBN: (纸本)9798331534622

Edge computing fulfills the urgent need of users for low-latency and high-quality computing services by transferring tasks from end devices to the edge side of the network for processing through task offloading techniques. However, edge computing still faces many challenges during task offloading. Considering that most task offloading strategies only optimize a single objective, this paper constructs a multi-objective optimization task offloading model, which integrates multiple metrics such as task offloading failure rate, task processing time, and load balancing. In order to solve the optimal solution of this model, this paper proposes a hybrid meta-heuristic algorithm based on greedy random adaptive search procedure (GRASP) and genetic algorithm (GA), called GAGRA. experimental results show that compared with genetic algorithm, ant colony algorithm, and simulated annealing algorithm, GAGRA enhances the task offloading failure rate, the task processing time, and load balancing respectively by 4.28%, 4.94% and 5.02%. these results validate the effectiveness of the task offloading strategy proposed in this paper. © 2024 ieee.

关键词： Simulated annealing

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Review of intelligent Methods for Sign Language-to-Speech Translation 4

Review of Intelligent Methods for Sign Language-to-Speech Tr...

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4th ieee international conference on Advanced Learning Technologies for Education and Research, ICALTER 2024

作者： Trujillo, Edita Chafloque Cajusol Castillo, Luis Felipe Aquino, Juri Universidad Tecnológica del Perú Systenms and Computer Engineering Chiclayo Peru Universidad Tecnológica del Perú Dirección de Investigación Chiclayo Peru Universidad Tecnológica del Perú Docente of Systems and Computer Engineering Chiclayo Peru

ISBN: (纸本)9798331510244

In today's digital age, technology has significantly transformed communication. However, for the deaf community, the communication barrier remains a persistent challenge. this article addresses the critical need to develop intelligent systems that translate sign language into speech, highlighting its potential to improve the social inclusion of people with hearing impairment. the study conducts a systematic review of advanced methods, such as the use of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to identify promising techniques and persistent challenges in this field. the research is based on the analysis of 32 articles selected using strict inclusion and exclusion criteria, following the PRISMA statement. the results reveal that these systems can improve the autonomy of deafblind people, facilitating their access to essential services and promoting their social and occupational inclusion. Furthermore, it highlights the need for solutions adapted to specific local contexts due to the geographical variability in the prevalence of hearing impairment. this work not only contributes to scientific knowledge, but also lays the foundation for the development of more effective and accessible technologies, potentially transforming areas such as education, healthcare and employment for the deaf community. © 2024 ieee.

关键词： intelligent systems

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