检索结果-内蒙古大学图书馆

An Arrhythmia Intelligent Recognition Method Based on a Multimodal Information and Spatio-Temporal Hybrid Neural Network Model

引用

computers, Materials & Continua 2025年第2期82卷 3443-3465页

作者： Xinchao Han Aojun Zhang Runchuan Li Shengya Shen Di Zhang Bo Jin Longfei Mao Linqi Yang Shuqin Zhang School of Computer Science Zhongyuan University of TechnologyZhengzhou450007China International Joint Laboratory for AI Interpretability and Reasoning Applications Zhengzhou450007China School of Foreign Languages Zhengzhou University of Economics and BusinessZhengzhou450099China

Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to perform multi-perspective learning of temporal signals and Electrocardiogram images, nor can they fully extract the latent information within the data, falling short of the accuracy required by clinicians. Therefore, this paper proposes an innovative hybrid multimodal spatiotemporal neural network to address these challenges. The model employs a multimodal data augmentation framework integrating visual and signal-based features to enhance the classification performance of rare arrhythmias in imbalanced datasets. Additionally, the spatiotemporal fusion module incorporates a spatiotemporal graph convolutional network to jointly model temporal and spatial features, uncovering complex dependencies within the Electrocardiogram data and improving the model’s ability to represent complex patterns. In experiments conducted on the MIT-BIH arrhythmia dataset, the model achieved 99.95% accuracy, 99.80% recall, and a 99.78% F1 score. The model was further validated for generalization using the clinical INCART arrhythmia dataset, and the results demonstrated its effectiveness in terms of both generalization and robustness.

关键词： Multimodal learning spatio-temporal hybrid graph convolutional network data imbalance ECG classification

来源：评论

学校读者我要写书评

暂无评论

MACPGANA: design of a highly efficient multimodal agriculture commodity price prediction model via generative adversarial networks & autoencoders

引用

international Journal of Information technology (Singapore) 2025年第4期17卷 2355-2368页

作者： kambo, Rubi Pillai, Jyothi Soni, Sunita Urkude, Giridhar Department of Computer Science and Engineering Bhilai Institute Technology Chhattisgarh Durg India Department of Computer Science and Engineering Rungta College of Engineering and Technology Chhattisgarh Bhilai India Symbiosis Institute of Technology Nagpur Campus Symbiosis International(Deemed University) Pune India Department of Computer Applications Bhilai Institute of Technology Durg Chhattisgarh India

This paper presents MACPGANA, a novel multimodal agriculture commodity price prediction model leveraging Generative Adversarial Networks (GAN) and Autoencoders (AEs). The model integrates multimodal data to extract and represent features efficiently, employs GAN for feature selection, and uses predictive autoencoders to estimate inter-day price movements. A Q-Learning-based feedback loop ensures continuous optimization of prediction performance. MACPGANA achieves high accuracy, precision, and recall while maintaining low computational complexity, making it suitable for real-time and large-scale applications. The model’s effectiveness is demonstrated across diverse commodities, highlighting its potential for scalable and efficient agricultural price prediction. © Bharati Vidyapeeth's Institute of computer applications and Management 2025.

关键词： Agriculture commodity price prediction Autoencoders (AE) Generative adversarial networks (GAN) Multimodal feature extraction Q-learning optimization Real-time price forecasting

来源：评论

学校读者我要写书评

暂无评论

引用

1st IEEE international Conference on Contemporary Computing and Communications, InC4 2023

作者： Sharma, Divya Sharma, Shilpa Patil, Harshal Bhatnagar, Vaibhav Manipal University Jaipur Department of Computer Applications Jaipur India Symbiosis Institute of Technology Symbiosis International Computer Science and Engineering Pune India

ISBN: (纸本)9798350335774

Image dehazing and image defogging work towards the same goal, which is to reconstruct hazy or foggy images by eliminating noise. Among the many dehazing and defogging algorithms available, Dark Channel Prior (DCP) is among the most effective algorithm. DCP employs the dark pixels from the noisy image to perform image reconstruction using the standard four-step process. In this paper, we implement DCP single image dehazing for license plate images. Specifically, the transmission map refinement was implemented using the guided filter. The implemented model performs the DCP implementation along with its five important parameter evaluations and analyzes the performance. The paper concludes with a comparative analysis for five parameters that are patch size, epsilon value, window radius, value of and finally pixel values. © 2023 IEEE.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Enabling Smart Home Energy Management through Gesture-Based Control and IoT technology

Enabling Smart Home Energy Management through Gesture-Based ...

引用

2023 international Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Rambe, Khairul Hawani Ou, Chia-Ho International Master Program in Information Technology and Applications Sweden National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

The Internet of Things (IoTs) have become ubiquitous in all aspects of public needs today. The application of IoT technology is crucial for promoting energy-saving behavior. This paper presents a control system used for smart home devices based on hand gesture control and Android applications. The hardware design uses the ESP32 microcontroller, which has an in-chip Wi-Fi module, making it very suitable for creating IoT application systems. The software was designed using the Arduino IDE, and the application display design was developed using Kodular Creator, which is used to control the lamps and switches. The experiment results show that the electrical equipment can be activated using the Android application with gesture sensors by waving down, up, left, and right. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Systematic Review of GAN for Enhancing Efficiency in AI in Gaming

Systematic Review of GAN for Enhancing Efficiency in AI in G...

引用

2024 international Conference on Advances in Computing Research on science Engineering and technology, ACROSET 2024

作者： Singh, Jasdeep Islam, Sardar M. N. Tewatia, Manav Garg, Deepanshu Fatima, Neda School of Computer Applications Manav Rachna International Institute of Research and Studies Faridabad India Victoria University Department of Computer Science and Engineering Melbourne Australia School of Engineering and Technology Manav Rachna International Institute of Research and Studies Faridabad India

ISBN: (纸本)9798350388800

A thorough analysis of Generative Adversarial Networks (GANs) and how they might be used to improve AI gaming efficiency is presented in this research. Game developers now have never-before-seen possibilities for innovation, immersion, and personalization thanks to GANs, which have become a potent tool for producing realistic data samples across a variety of fields. This review investigates the architecture, training methods, applications, difficulties, and potential future directions of GANs in AI gaming through a thorough analysis of the body of research and publications. The review demonstrates how GANs can transform the game industry by highlighting their many uses in procedural content generation, texture synthesis, character animation, environment design, and content customization. Nevertheless, there are certain difficulties in integrating GANs into AI games, such as computational resources, mode collapse, training instability, and assessment *** well as legal matters. To tackle these obstacles, multidisciplinary research endeavors and cooperation across academic institutions, corporate entities, and regulatory agencies are necessary. Going forward, new avenues for study and developments in GAN technology hold great potential for getting over these roadblocks and opening up fresh possibilities in AI gaming. We can create a future where AI powered gaming experiences change the parameters of interactive entertainment and provide players globally with more engaging, varied, and personalized gaming experiences by utilizing the possibilities of GANs and addressing the related obstacles. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

A Haar-Cascading and Deep Learning Driven Enhanced Mechanism on Cloud Platform for Real-Time Facial Emotion Detection 5

A Haar-Cascading and Deep Learning Driven Enhanced Mechanism...

引用

5th international Conference on Energy, Power, and Environment, ICEPE 2023

作者： Kumar, Anil Navdeep Kumar, Adarsh Swain, Smruti Rekha Gupta, Ishu Singh, Ashutosh Kumar National Institute of Technology Department of Computer Applications Kurukshetra India International Institute of Information Technology Department of Computer Science Bangalore India Indian Institute of Information Technology Madhya Pradesh Bhopal India

ISBN: (纸本)9798350313123

Real-time emotion detection utilizes computer vision that aims to recognize and categorize emotions. However, it contains challenges, including the intricate nature of emotions and the variations in their expression across individuals. The accuracy of the system can also be affected by environmental factors such as background noise, lighting, and other people. Having access to a diverse and comprehensive dataset is essential for training algorithms that can accurately detect emotions in real time. In order to tackle these challenges, we utilized CNN and seven emotions to identify their corresponding facial expressions. By implementing appropriate activation functions like ELU, ReLU, and Leaky ReLU, and training with the dataset Facial Expression Recognition 2013 (FER-2013) that contains over 30,000+ images of facial expressions and emojis, as we increase the epoch the accuracy of this model increases, we achieved an impressive accuracy of 94.74% by using ReLU on 100 enochs. © 2023 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Mathematical Morphology Adopted Automatic Detection of Ground Glass Opacities in Lung CT Images of COVID-19 Patients

Mathematical Morphology Adopted Automatic Detection of Groun...

引用

2023 international Conference on Intelligent Systems, Advanced Computing and Communication, ISACC 2023

作者： Chatterjee, Soma Chatterjee, Rohit Kamal Goswami, R.T. Techno International New Town Dept. of Computer Applications Kolkata India Birla Institute of Technology Dept. of Computer Science & Engineering Mesra Ranchi India Techno International New Town Dept. of Computer Science Kolkata India

ISBN: (纸本)9798350399387

The severity of the nCOVID infection relies on the presence of Ground Glass Opacities (GGO) present in the patient's chest CT scan images. Although, detecting and delineating the precise boundaries of GGO in the chest CT images is challenging. Here, we proposed a fast and novel technique to automatically segment the regions containing GGO in lung CT images using mathematical morphology. We have tested our algorithm on the chest CT images of 145 Covid-positive cases. This unique segmentation approach correctly segments the lung field from chest CT images and identifies GGO with average sensitivity, specificity, and accuracy of 96.89%, 95.23%, and 97.22%, respectively. We used expert radiologists' hand-curated segmentation of GGO as ground truth for quantificational performance analysis. Our research results indicate that this algorithm performs well found in the literature. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Forecasting IPL Score Using Machine Learning Techniques

Forecasting IPL Score Using Machine Learning Techniques

引用

2024 international Conference on Artificial Intelligence and Quantum Computation-Based Sensor applications, ICAIQSA 2024

作者： Panchal, Riddhi Sakarkar, Gopal Shelke, Nilesh Pimpalkar, Amit MITWPU Department of Computer Science and Applications Maharashtra Pune India Symbiosis Institute of Technology Nagpur Campus Symbiosis International Deemed University Pune India Maharashtra Nagpur India

ISBN: (纸本)9798331517953

The IPL, which stands for Indian Premier League, has become one of the most widespread and fought over Twenty20 cricketers in the world, which borrows the interest of its audience with its ever-changing and chaotic nature. In this research paper, the researchers aim to employ various machine learning techniques to predict the cricket scores of an IPL match, recording valuable insights aimed at enhancing the understanding of the sport and providing useful insights for the sporting teams and the fans as well as the analysts. The work aims to develop and test computational intelligence models appropriate for estimating IPL match total scores using modern technologies such as machine learning and artificial intelligence based on historical match scores, player statistics and match context. Among the methods used were ensemble techniques, such as neural and regression networks, to investigate complex patterns within the dataset and increase accuracy in predictive performance. As part of modelling, we harnessed a dataset that covers several seasons of the IPL that includes performance indicators of players, match characteristics, and necessary background information like the weather and venue of the game. Models are evaluated using the same dataset, but the target for prediction was never seen during training, thus ensuring that the model was accurate, recall, precision, and overall performance were optimal during training. Standard metrics such as MAE-Mean Absolute Error, MSE-Mean Square Error and RMSE Root Mean Squared Error measure the predictability of models. Lastly, we compared the algorithms to identify those that better predict IPL cricket scores. Knowledge derived from our research is rich since it hails from cricket match result factors highlighting the need to consider a player's form, teamwork, and extra influences from the weather. From its ability to demonstrate the viability and effectiveness of machine learning to predict scores in the game of cricket's IP

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

A Deep Dive into Existing Lip Reading Technologies

A Deep Dive into Existing Lip Reading Technologies

引用

2024 international Conference on Artificial Intelligence and Quantum Computation-Based Sensor applications, ICAIQSA 2024

作者： Khekare, Ganesh Majumder, Goutam Shelke, Nilesh Sakarkar, Gopal Buchade, Siddhant School of Computer Science and Engineering Vellore Institute of Technology Vellore India Symbiosis Institute of Technology Nagpur Campus Symbiosis International Deemed University Pune India Dr. Vishwanath Karad MIT World Peace University Department of Computer Science and Applications Pune India

ISBN: (纸本)9798331517953

Lip reading, or Visual Speech Recognition (VSR), can revolutionize communication for those with hearing loss and in noisy environments. The researchers are trying to create advanced VSR systems using Deep learning models to overcome challenges. But still, several difficulties are there such as different shapes of lips during the video and different lightning conditions that can make deciphering or visualization difficult. Deep learning with the help of Convolutional Neural Networks (CNNs) helps to identify the exact shape and movement of a lip from a video frame. The continuous flow of lip movements in the video is handled by Recurrent Neural Networks (RNNs) which help in identifying words. However, RNNs are not good enough to remember the historical data. This issue is resolved by using Long Short Term Memory (LSTM) in the proposed research work. LSTMs have an additional internal memory that helps to store the history information for a longer period which helps to predict lip movement accurately even in rapid speech. The GRID and LRW datasets are used to generate the results. Additionally, VSR could improve video conferencing, allowing for natural communication even with compromised microphone quality. The impact of VSR extends beyond human-to-human and human-computer interaction. Frameworks like Streamlit offer a glimpse into the future, enabling the development of user-friendly lip reading applications. Deep learning unlocks the power of lip reading, paving the way for a future where communication go beyond the limitations of sound. © 2024 IEEE.

关键词： Video conferencing

来源：评论

学校读者我要写书评

暂无评论

Decoding the Mind's Symphony: A Mathematical Exploration of Mindfulness Meditation and Visual Working Memory

Decoding the Mind's Symphony: A Mathematical Exploration of ...

引用

2023 IEEE international Conference on Network, Multimedia and Information technology, NMITCON 2023

作者： Mahanta, Abhishriya Sakshi Verma, Gunjan Gauhati University Institute of Science and Technology Department of Information Technology Guwahati India School of Computer Applications Manav Rachna International Institute of Research and Studies Faridabad India

ISBN: (纸本)9798350300826

The main aim of this study was to investigate the effects of mindfulness meditation training on information processing during a working memory task involving challenging visual stimuli. Participants, consisting of a meditation group and a matched control group, underwent an intensive one-month mindfulness meditation program. The working memory task, specifically a delayed face recognition task, was administered both before and after the training period. response time (RT), RT variability, and accuracy were measured as performance indicators. To gain insights into the underlying mechanisms, mathematical modeling techniques utilizing the EZ Diffusion (EZD) and Noisy Exemplar models (NEM) were employed. The application of the EZD model revealed noteworthy findings for the meditation group, including an increase in drift rate (indicating improved perceptual information quality) and a decrease in the decision boundary. Furthermore, the Noisy Exemplar model analysis demonstrated a decrease in encoding noise (indicating reduced attentional lapses) for the meditation group. These results suggest that mindfulness meditation training enhances working memory performance by boosting attention and perceptual information quality. By combining behavioral tasks and mathematical modeling approaches, this study offers a comprehensive understanding of the cognitive effects of mindfulness meditation. The findings highlight the potential of mindfulness training to improve attentional processes and enhance working memory. © 2023 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：