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检索条件"任意字段=2023 International Conference on Computer Engineering and Distance Learning, CEDL 2023"

共 40847 条记录，以下是4201-4210 订阅

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LPCUNet:A Lightweight Pure CNN UNet for Efficient Urban Scene Remote Sensing Semantic Segmentation 4

LPCUNet:A Lightweight Pure CNN UNet for Efficient Urban Scen...

引用

4th international conference on computer Vision, Image and Deep learning, CVIDL 2023

作者： Liu, Bing Wu, Huizhu Bao, Xueliang Zhong, Zhaohao College of Computer Science and Engineering Changchun University of Technology College of Computer Science and Technology Jilin University Changchun China College of Computer Science and Engineering Changchun University of Technology Changchun China Aviation University of Air Force Changchun China

ISBN: (纸本)9798350326444

Semantic segmentation, a fundamental task in computer vision, has developed rapidly in recent years. Semantic segmentation of remote sensing urban scene images, utilized in tasks such as land cover mapping, urban change detection, environmental preservation, and economic assessment, has also received much attention. In order to extract global semantic features, recent research has focused on combining transformers with CNN, which have great potential in global information modeling, for semantic segmentation models. However, the hybrid method of CNN and Vision Transformer still suffers from low latency. And the MLP of the visual transformer results in many parameters. To address these issues, we propose a lightweight pure CNN UNet(LPCUNet) model, which introduces a sizeable convolutional kernel to capture the global context. Moreover, a simple fusion module dynamically fuses local and global features. Extensive experiments show that our proposed method achieves state-of-the-art performance while faster latency. More precisely, the LPCUNet model demonstrated impressive performance with 83.3% and 86.4% mean Intersection over Union (mIoU) scores on the Vaihingen and Potsdam datasets respectively. © 2023 IEEE.

关键词： Semantic Segmentation

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Toxic Comment Analyzer using BERT: A Deep learning Approach for Toxicity Detection 2

Toxic Comment Analyzer using BERT: A Deep Learning Approach ...

引用

2nd international conference on Informatics, ICI 2023

作者： Singh, Richa Kashyap, Rekha Sharma, Vikrant Muradnagar India Graphic Era Hill University Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350343830

With the good hike of social and communication platforms, a significant increase in the volume of user-generated content is produced. Unfortunately, this surge in online interactions has also led to an increase in toxic and offensive comments. Toxic comments not only contribute to a negative online environment but also have the potential to harm individuals and communities. Consequently, the development of automated methods for detecting toxic comments has become imperative. In this research paper, we propose a toxic comment analyzer using BERT to address this issue. Our approach demonstrates the effectiveness of leveraging pre-Trained language models for identifying toxic language, with promising results of 97% accuracy on benchmark datasets. © 2023 IEEE.

关键词： Deep learning

来源：评论

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Work-In-Progress: Investigate Eye-Tracking Metrics and Effectiveness of Visual learning Aids in Online learning Environments for Students with learning Disabilities Using Machine learning 53

Work-In-Progress: Investigate Eye-Tracking Metrics and Effec...

引用

53rd IEEE ASEE Frontiers in Education international conference, FIE 2023

作者： Liu, Yuexin Lu, Wei Zavareh, Amir Tofighi Zoghi, Ben Texas A&m University Department of Etid College Station United States

ISBN: (纸本)9798350336429

This Work-In-Progress study proposes a novel approach to explore the learning behaviors of students with learning disabilities in online learning environments by investigating eye-tracking metrics and effectiveness of visual learning aids. It builds on previous research that suggests that students with learning disabilities often face difficulties in online learning environments due to the lack of visual cues and their limited ability to interact with the learning material. The use of machine learning to analyze eye-tracking data and visual learning aids can provide insights into how students with learning disability interact with online learning materials, with the goal of improving the learning outcomes as well as informing the design of constructive teaching strategies and seeking to expand this research to the online learning context. © 2023 IEEE.

关键词： data correlation factor analysis K-12 philosophy of engineering education STEM

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Enhancing Wheelchair Communications Utilizing Thread Protocol for Improved Patient Safety 9

Enhancing Wheelchair Communications Utilizing Thread Protoco...

引用

9th IEEE international Smart Cities conference, ISC2 2023

作者： Khattak, Sohaib Bin Altaf Farman, Haleem Nasralla, Moustafa M. Esmail, Maged Abdullah College of Engineering Prince Sultan University Smart Systems Engineering Lab Department of Communications and Networks Engineering Riyadh Saudi Arabia

ISBN: (纸本)9798350397758

This paper presents an efficient framework for smart wheelchair communications within a rehabilitation center, utilizing the Thread protocol to enhance patient safety and healthcare management. The proposed system aims to establish bidirectional communication between wheelchairs and other healthcare devices in the center. The framework comprises two types of nodes: wheelchairs, equipped with sensors for physio-logical measurements and Thread communication modules, and fixed nodes, including Thread routers forming a mesh network for robust connectivity. A Thread border router acts as a bridge between the internal Thread network and a centralized health-care database through Wireless Local Area Network (WLAN). This multi-tiered communication system integrates data collection, local communication, aggregation, and routing, facilitating seamless data exchange for improved patient care and overall healthcare management. A testbed is developed to evaluate the performance of the proposed framework by considering packet loss and jitter while increasing the distance among wheelchair and Thread router. Performance evaluation of the network was conducted across distances ranging from 1 to 40 meters, utilizing a 20 kbps bitrate. The results demonstrate the efficacy and reliability of the proposed framework, making it a promising solution for advancing healthcare in rehabilitation centers. © 2023 IEEE.

关键词： Electronic data interchange

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Implementation of Summary-Connection-Prediction (SCP) Instructional Strategy in Flipped Classroom with Moodle: Investigate Preservice Teachers' Acceptance and Beliefs 23

Implementation of Summary-Connection-Prediction (SCP) Instru...

引用

8th international conference on Sustainable Information engineering and Technology, SIET 2023

作者： Hariyanti, Uun Batita, Maurish Sofie Rahmi Suharsono, Aswin Department of Information System Faculty of Computer Science Universitas Brawijaya Indonesia

ISBN: (纸本)9798400708503

This study investigated the implementation of summary-connection-prediction (SCP) instructional strategy on students' report tasks before the class under the flipped classroom learning design with Moodle. A total of 106 undergraduate students who enrolled in the Teaching and learning Theory course participated in this study. A questionnaire based on the technology acceptance model (TAM) and open-ended interview questions were used to collect the data. Following the results, it is known that the preservice teachers have high positive acceptance of SCP strategy. Further, perceived ease of use and perceived usefulness significantly predict behavioral intention, which follows the relationship direction in TAM. Regarding the thematic analysis of interview data, three themes are elaborated to obtain in-depth information about what preservice teachers' beliefs when implementing this strategy. © 2023 ACM.

关键词： Forecasting

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Emotion Detection in Speech: A CNN Neural Network Approach

Emotion Detection in Speech: A CNN Neural Network Approach

引用

2023 IEEE international conference on Network, Multimedia and Information Technology, NMITCON 2023

作者： Shashidhar, R. Shruthi, B.M. Manjunath, A.S. Roopa, M. Sharma, Neha Singh, Pardeep Jss Science and Technology University Dept. of Electronics and Communication Engineering Mysuru India Jss Science and Technology University Dept. of Computer Science and Engineering Mysuru India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Computer Science and Engineering Graphic Era Hill University Dehradun India

ISBN: (纸本)9798350300826

Speech emotion recognition is an area of research dedicated to identifying and categorizing emotions expressed through speech. Its purpose is to comprehend and interpret the emotional content conveyed in spoken words, leveraging signal processing techniques, feature extraction algorithms, and machine learning models. The ultimate aim is to apply this knowledge in diverse applications such as human-computer relation, affective computing, and mental health diagnosis. Although the complexity and variability of emotional speech present significant challenges, recent years have witnessed notable progress through the development of advanced algorithms and the utilization of extensive training datasets. Here we proposed a CNN network pattern for speech emotion recognition for the bench mark datasets and got the accuracy of 88% for the convolutional neural network model. © 2023 IEEE.

关键词： Data visualization

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System for Predicting the Diabetes using Machine learning Techniques 2

System for Predicting the Diabetes using Machine Learning Te...

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2nd international conference on Electronics and Renewable Systems, ICEARS 2023

作者： Alagarsamy, Saravanan Muthuvel, P. Kumar, K. V. Sudheer Reddy, M. Madhusudhan Naidu, M. Mallikarjuna Kumar, M. Venkat Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Anand Nagar India

ISBN: (纸本)9798350346640

Diabetes needs to be managed constantly because it is a chronic and complicated medical illness. The importance of creating cutting-edge solutions to aid in the management of this condition is growing as diabetes prevalence rises. This study suggests using machine learning to manage healthcare costs and anticipate the onset of diabetes. To be more precise, we suggest combining supervised and unsupervised learning techniques to deliver patient-specific real-time forecasts and track the development of the disease. Using publicly accessible diabetes datasets, we will assess the performance of the suggested approach and contrast the findings with current techniques. In addition, we'll talk about how applying machine learning approaches could help with diabetes management. The goal of this paper is to present the potential of machine learning for enhancing diabetes treatment and to offer a framework for further investigation in this field. © 2023 IEEE.

关键词： Predictive analytics

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COLLABORATIVE learning IN STEAM TEACHING FOR STUDENTS IN THE CENTRAL AMAZON 21

COLLABORATIVE LEARNING IN STEAM TEACHING FOR STUDENTS IN THE...

引用

21st international conference on e-Society, ES 2023 and 19th international conference on Mobile learning, ML 2023

作者： Rodrigues, Juliana Gisele Corrêa de Medeiros Silva, Adan Sady da Silva Junior, Jucimar Maia Post-graduation program in Biodiversity and Biotechnology from BIONORTE Amazonas State University Brazil Dept. of Meteorology Amazonas State University Brazil Dept. of Computer Engineering Amazonas State University Brazil

ISBN: (纸本)9789898704474

The State of Amazonas has one of the most modern industrial and technological centers in Latin America. As a result, the search for skilled professionals for this job market is constantly growing. It is believed that STEAM teaching is an important tool to improve engagement, creativity, innovation, problem-solving skills, and other cognitive benefits generating more skilled professionals in the technology market. One approach that can be applied to STEAM teaching in schools is collaborative learning through maker culture. From mobile labs the STEM Academy Project takes STEAM teaching to high school students in public schools in the state of Amazonas. In the courses taught, collaborative learning is also applied in order for students to understand topics such as basic electronics, robotics, and programming, thus stimulating students' social skills and shared mutual learning, and attracting them to degree courses in STEAM fields. © 2023 Proceedings of the international conferences on e-Society 2023, ES 2023 and Mobile learning 2023, ML 2023. All rights reserved.

关键词： Students

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A Secure Client Video Deduplication Scheme Based on 3D CNN 2

A Secure Client Video Deduplication Scheme Based on 3D CNN

引用

2nd international conference on Machine learning, Cloud Computing, and Intelligent Mining, MLCCIM 2023

作者： Li, Xue Wang, Zhong Liu, Yanfei Fan, Qinggang Chen, Jing Rocket Force University of Engineering Department of Basic Courses Xi'an China

ISBN: (纸本)9798350328530

With the advent of the era of big data, users are generally used to uploading local data to the cloud server to reduce the pressure of storage. This will lead to many duplicate data in the cloud server and form a large number of redundant, especially the existence of videos. To solve the problem of wasting storage space for duplicate videos, on the one hand, we propose a two-stream 3D CNN combined with triple metric method to construct a duplicate video detection scheme, when the threshold is 3.6, the recall rate can reach 97.1905%, while the false positive rate is only 0.0743%, which is better than the I3D deduplication scheme. Through the Chamfer distance matching algorithm for two-stream video features, compared with the duplicate video detection model based on I3D network with EMD distance in terms of false positive rate, recall rate and time cost, it achieved a good video deduplication effect. In addition, some videos are used to test the deduplication performance of Hamming distance, EMD distance and Chamfer distance, the results show that the Chamfer similarity distance algorithm has a higher recall rate and a lower false positive rate than the other two methods. On the other hand, we propose a video ownership proof scheme based on random block fusion. The server and the client respectively perform random cropping operations and fusion on the video frames, then generate verification tags and ownership evidence. Finally the server calculates the distance to determine whether the client can pass the authentication. The experiment results show that the scheme has less time and storage overhead and can resist the spoofing attack of criminals. © 2023 IEEE.

关键词： Hamming distance

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VidSum-Video Summarization using Deep learning 2

VidSum-Video Summarization using Deep Learning

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2nd international conference on Informatics, ICI 2023

作者： Anand, Nishit Koshariya, Rupesh Kumar Garg, Varsha Jaypee Institute of Information Technology Noida Department of Computer Science Engineering and Information Technology Noida India

ISBN: (纸本)9798350343830

The aim of video summarization is to create a short summary video which captures the essence of the original video and contains all the important events of the original video. This is helpful because, now we don't have to go through the entire video and are able to get a gist of it from just a short summary video. Current Supervised learning video summarization methods, use Convolutional Neural Networks and some supervised learning techniques use Recurrent Neural Networks in addition to them. We propose VidSum, an architecture for Video Summarization using Deep learning. We combine Long Short Term Memory (LSTM) Networks with Convolutional Neural Networks to solve the problem of Video Summarization. Our deep learning model is able to find the temporal importance of video frames and is able to generate video summaries which are temporally coherent and contain the important parts of a video clip. In our testing, our model outperforms other models on the famous TVSum and SumMe datasets for the task of Video Summarization. © 2023 IEEE.

关键词： Long short-term memory

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