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

共 40714 条记录，以下是4711-4720 订阅

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Navigating online learning challenges and opportunities: Insights from small group of lecturers during pandemic 7

Navigating online learning challenges and opportunities: Ins...

引用

7th Information Systems international conference, ISICO 2023

作者： Faza, Ahmad Santoso, Harry Budi Hadi Putra, Panca O. Universitas Multimeia Nusantara Faculty of Engineering and Informatics Tangerang15810 Indonesia Universitas Indonesia Faculty of Computer Science Depok16424 Indonesia

The implementation of e-learning platforms in higher education offers opportunities to enhance education quality and increase access to flexible learning. However, challenges arise, including limited guidance for students, high dropout rates, and obstacles faced by instructors. This qualitative case study explores the challenges and opportunities of online learning from instructors' perspectives. Data was collected through a survey administered to 23 instructors, and thematic analysis was conducted to identify the themes of challenges and opportunities. Findings reveal challenges in interaction, practical session delivery, monitoring, assessment, and identity verification. Institutional support challenges include insufficient training and socialization. Individual Challenges encompass digital skills, health concerns, and fatigue. Technological challenges involve availability, integration, capacity, and network-related issues. Despite these challenges, online learning provides opportunities for time effectiveness, flexibility, personal development, innovative teaching methods, and collaboration with external experts. © 2023 The Authors. Published by Elsevier B.V.

关键词： E-learning

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Malicious URL Detection Using Machine learning 6

Malicious URL Detection Using Machine Learning

引用

6th international conference on Contemporary Computing and Informatics, IC3I 2023

作者： Kinger, Shakti Nirmal, Pranav Shrivastav, Ayush Sharma, Aniket Saindane, Sakshi University School of Computer Engineering Dr. Vishwanath Karad MIT World Peace Maharashtra Pune India

ISBN: (纸本)9798350304480

Malicious websites that can hurt users and steal personal information are now a serious problem that requires immediate attention. Machine learning techniques are widely utilized to accurately identify and categorize such websites. These models examine the static elements of the websites to find any potential flaws or hidden exploit code. This study assesses the effectiveness and accuracy of different machine learning models for identifying dangerous URLs. The autoencoder neural network had the lowest accuracy, at 61.50%, followed by the Multilayer Perceptrons (MLPs) model with an accuracy of 85.50%, and XGBoost with an accuracy of 85.35%. The study shows how well machine learning models work at identifying and stopping the spread of harmful websites. This study highlights the significance of using machine learning techniques to protect users from potential harm. © 2023 IEEE.

关键词： feature extraction feature selection machine learning Malicious URL detection

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Comprehensive Analysis and Research on the Mainstream Algorithm of Machine learning in Stock Trend Prediction

Comprehensive Analysis and Research on the Mainstream Algori...

引用

2023 IEEE international conference on Control, Electronics and computer Technology, ICCECT 2023

作者： Cai, Jiajing Zheng, Xiuyan Wang, Jiabin Meng, Shangyu Hainan Vocational University of Science and Technology College of Information Engineering Haikou China

ISBN: (纸本)9798350399028

The rapid growth of the equity market has progressively become an essential pillar of the nation's economy. The stock market can generate high returns. our research focuses on how to accurately foresee the stock price trend. In this paper, Fenghua high-tech stock data is chosen as the experimental data, and stock movements are predicted using the support vector machine (SVM) model, the LGBM model, and the random forests (FM) model. On the premise of empirical research, the prediction effect and accuracy of each model are demonstrated by integrating the prediction curve of each model with the evaluation indices RMSE, MAE, MAPE, and R2. The results indicate that the model based on random forest provides more accurate predictions. © 2023 IEEE.

关键词： Support vector machines

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BIRDS-BD: A Comprehensive Dataset for Bangladeshi Local Birds and Classification Using Vision Transformer with Transfer learning 26

BIRDS-BD: A Comprehensive Dataset for Bangladeshi Local Bird...

引用

26th international conference on computer and Information Technology, ICCIT 2023

作者： Rabby, Mahedi Hassan Ahmed, Kabir Rady, Fazla Rabby Akash, Abdul Kader Shahjalal University of Science and Technology Department of Computer Science and Engineering Sylhet Bangladesh

ISBN: (纸本)9798350359015

In this research, we present an extensive exploration of machine learning techniques applied to the detection and classification of 16 distinct bird species indigenous to Bangladesh. Leveraging the advanced Vision Transformer model, our study addresses the challenge of fine-grained bird identification, encompassing species such as Bashpati, Duel, Kak, Bok, Eagle, Kobutor, Bulbuli, Chorui, Finge, Kukil, Ghughu, Masranga, Myna, Shalik, Tia, and Tuntuni with 12800 image without including augmented image. This vast size of dataset enrich the research on this topic. Our approach involves training the Vision Transformer model on a diverse dataset of bird images collected across various regions of Bangladesh. The model's intrinsic architecture enables it to efficiently discern intricate features and patterns within the images, facilitating precise classification of the targeted bird species. We rigorously evaluate the model's performance in terms of precision, recall, and F1-score, revealing an impressive accuracy 92.03%. This research underscores the practicality and efficacy of machine learning techniques, particularly through the Vision Transformer model, for Bangladeshi bird detection and classification. The results not only contribute to the understanding of local bird diversity but also exemplify how cutting-edge technology can play a pivotal role in wildlife conservation and research within the region. © 2023 IEEE.

关键词： Bangladeshi Bird Classification Transfer learning Vision transformer

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A Study on Eye Tracking for Mobile Devices Using Deep learning 23

A Study on Eye Tracking for Mobile Devices Using Deep Learni...

引用

24th international conference on computer Systems and Technologies, CompSysTech 2023

作者： Le Hoang, Nam Porta, Marco Faculty of Information Technology Hanoi University Hanoi Viet Nam Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (纸本)9798400700477

While eye tracking technology has been around for several years, it has traditionally been implemented on personal computers using specific devices. Eye tracking through smartphones or tablets is much more challenging, because it involves the use of standard cameras and typically significantly fewer computational resources. In this paper, we present a study in which, based on a large dataset of face images acquired via mobile devices, we investigate the influence of some design choices (in particular, related to optimizers, color, and regularization techniques) on a deep learning convolutional architecture. We believe that the results obtained, although preliminary, can provide a useful contribution to a challenging and constantly evolving research field such as that of eye tracking for mobile appliances. © 2023 ACM.

关键词： Eye tracking

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A Non-Contact Human-computer Interaction Method Based on Gaze 13

A Non-Contact Human-Computer Interaction Method Based on Gaz...

引用

13th IEEE international conference on Electronics Information and Emergency Communication, ICEIEC 2023

作者： Chen, Wenting Sun, Xin School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350331714

Gaze interaction has a broad application prospect in the field of human-computer interaction. Traditional gaze interactive sensing devices are expensive and inconvenient to use. The gaze point estimation model based on deep learning is complex and poor in generalization, and difficult to deploy on intelligent terminals. This paper proposed a gaze point estimation network based on deep learning and its personalized calibration method which can adapt to different devices and users. The gaze point estimation network used eye images, eye corners and the camera relative to screen position as inputs to extract feature embeddings. Then the feature embeddings were fed to the trained personalized SVR model to obtain the final gaze point estimation. Tests were conducted on both the self-built gaze dataset and the open source dataset to verify the effectiveness of the proposed model in terms of accuracy and latency. On this basis, a simple human-computer interaction application was implemented by analyzing the fixation point and identifying the user's control behavior. © 2023 IEEE.

关键词： Eye tracking

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Defect Detection of Wood Grain Images with Image Gradient Applied to AE-based generation 6

Defect Detection of Wood Grain Images with Image Gradient Ap...

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6th IEEE international conference on Knowledge Innovation and Invention, ICKII 2023

作者： Si, Jongwook Kim, Sungyoung Kumoh National Institute of Technology Department of Computer Ai Convergence Engineering Gumi Korea Republic of Kumoh National Institute of Technology Department of Computer Engineering Gumi Korea Republic of

ISBN: (纸本)9798350323535

Detecting and managing various types of defects that occur in the manufacturing process is important for product quality control. Detecting flaws in product presentation is an ongoing research topic in computer vision. Recently, deep learning technology has been used to improve defect detection performance compared to traditional computer vision methods. In this study, we proposed a new method for detecting defects on the surface of wooden boards using image reconstruction with an autoencoder-based model and image gradient filters in image processing using edge detection. Although the reconstruction performance of the autoencoder is significantly inferior to the newest technologies, this characteristic is used to remove noise from input images. We used the publicly available anomaly detection dataset, MV-Tec AD, for training and evaluation and presented experimental results focusing on the "Wood"category. The proposed method in this study demonstrated better detection performance with image processing. © 2023 IEEE.

关键词： Image reconstruction

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A Logical Investigation of Stock Market Prediction and Analysis using Supervised Machine learning Algorithm 1

A Logical Investigation of Stock Market Prediction and Analy...

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1st IEEE international conference on Networking and Communications, ICNWC 2023

作者： Dhanalakshmi, R. Kumar, V. Vasantha Basha, Saleem Vijayaraghavan, N. Vellore Institute of Technology School of Computer Science and Engineering Chennai India Mazoon University College Computing and Informatics Department Muscat Oman KCG College of Technology Department of CSE Chennai India

ISBN: (纸本)9798350336009

In the Field of computer science, artificial intelligence (AI) is a broad field, which is concerned with structuring smart products and machines able to perform tasks which require the intellectual capability of humans. Artificial Intelligence is in need for Stock trading's future. Robotic advisers examine millions of pieces of data using artificial intelligence and carry out the analysis at the best possible price. Market forecasts are more precise and effective thanks to the analysts. For providing higher returns, the trading firms efficiently mitigate the risk using Artificial Intelligence Techniques. Our proposed Stock Market system is a Web Application which uses the Random Forest Algorithm. The Random Forest Algorithm comes under Supervised learning. With the system, one can forecast the stock prices for the subsequent days. © 2023 IEEE.

关键词： Forecasting

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DASENet:A Detail Aware U-Net with Shuffle Excitation for Retinal Vessel Segmentation 6

DASENet:A Detail Aware U-Net with Shuffle Excitation for Ret...

引用

6th international conference on Software engineering and computer Science, CSECS 2023

作者： Zhu, Jiqiang Lan, Zhangli Wen, Xinpeng Cai, Songbai Xu, Yuantong School of Information Science and Engineering Chongqing Jiaotong University Chongqing China

ISBN: (纸本)9798350306378

Retinal vessel images serve as valuable tools for early screening and timely diagnosis of ocular disorders. With the advancement of deep learning, a multitude of segmentation models have been utilized for retinal vessel image segmentation tasks. However, the challenge of enhancing feature expression capabilities and refining the accuracy of retinal blood vessel segmentation persists. In this study, we propose an end-to-end retinal vessel segmentation network named DASENet. To capture finer vessel details and enhance feature expression capabilities, a detail aware block (DAB) is proposed for feature extraction and to heighten the network's focus on vessel information. Moreover, shuffle excitation (SE) within skip connections is proposed to capture contextual dependencies between features and reduce differences between feature maps at different depths. Experimental results on the DRIVE, STARE and CHASE_DB1 datasets demonstrate that our DASENet outperforms other related advanced work. © 2023 IEEE.

关键词： Image segmentation

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Research on single-pixel imaging reconstruction algorithm based on residual attention channel network 2

Research on single-pixel imaging reconstruction algorithm ba...

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2nd international conference on Image Processing, computer Vision and Machine learning, ICICML 2023

作者： Zhang, Yi Gao, Zijun Dalian Polytechnic University College of Information Science and Engineering Dalian China

ISBN: (纸本)9798350331417

Single-pixel imaging (SPI) refers to the complete image obtained by processing and reconstructing the data acquired from the image, however, the traditional SPI reconstruction algorithm reconstructs the image with more detail texture missing and serious artifacts at low sampling rates. To address this problem, this paper proposes an SPI reconstruction algorithm based on residual in-channel attention block (RICAB-GAN). In the proposed reconstruction algorithm, we improve the residual block in the generator network by adding channel attention (CA), which enables the network to notice more texture details in the image. In the discriminator network we remove all the BN layers to reduce the artifacts in the image and improve the generalization ability of the model. Through simulation experiments, our algorithm improves psnr by 1-5dB, ssim by 0.1-0.3, and retains image details and textures better than traditional SPI algorithms at low sampling rates. © 2023 IEEE.

关键词： channel attention generative adversarial networks residual blocks SPI

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