检索结果-内蒙古大学图书馆

Ensembles of Deep Learning Framework for Stomach Abnormalities Classification

computers, Materials & Continua 2022年第3期70卷 4357-4372页

作者： Talha Saeed Chu Kiong Loo Muhammad Shahreeza Safiruz Kassim Department of Artificial Intelligence Faculty of Computer Science and Information TechnologyUniversiti Malaya50603 Kuala LumpurMalaysia

Abnormalities of the gastrointestinal tract are widespread worldwide ***,an effective way to diagnose these life-threatening diseases is based on endoscopy,which comprises a vast number of ***,the main challenge in this area is that the process is time-consuming and fatiguing for a gastroenterologist to examine every image in the ***,this led to the rise of studies on designingAI-based systems to assist physicians in the *** several medical imaging tasks,deep learning methods,especially convolutional neural networks(CNNs),have contributed to the stateof-the-art outcomes,where the complicated nonlinear relation between target classes and data can be learned and not limit to hand-crafted *** the other hand,hyperparameters are commonly set manually,which may take a long time and leave the risk of non-optimal hyperparameters for *** effective tool for tuning optimal hyperparameters of deep CNNis Bayesian ***,due to the complexity of the CNN,the network can be regarded as a black-box model where the information stored within it is hard to ***,Explainable Artificial Intelligence(XAI)techniques are applied to overcome this issue by interpreting the decisions of the CNNs in such wise the physicians can *** play an essential role in real-time medical diagnosis,CNN-based models need to be accurate and interpretable,while the uncertainty must be ***,a novel method comprising of three phases is proposed to classify these life-threatening *** first,hyperparameter tuning is performed using Bayesian optimization for two state-of-the-art deep CNNs,and then Darknet53 and InceptionV3 features are extracted from these fine-tunned ***,XAI techniques are used to interpret which part of the images CNN takes for feature *** last,the features are fused,and uncertainties are handled by selecting entropybased *** experimental results show that the

关键词： Gastrointestinal tract deep learning Bayesian optimization hyperparameters explainable AI uncertainty handling feature fusion

来源：评论

学校读者我要写书评

暂无评论

Fraud Detection in Financial Domain using Machine Learning

Fraud Detection in Financial Domain using Machine Learning

引用

2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Pathak, Nilotpal Singhal, Swasti Gl Bajaj Institute of Technology and Management Department of Computer Science Engineering Greater Noida India Kiet Group of Institutions Department of Computer Science and Information Technology Ghaziabad India

ISBN: (纸本)9798350322309

Digital fraud has become a menace in every industry. It is critical for any firm to have a concentrated focus on detecting and preventing fraudulent activities. Security is a priority. The way we communicate has changed dramatically as a result of digitization. A simple click of a mouse, complete our day-to-day transactions. On the other hand, it has created concerns from swindlers who take advantage of absent protections in current financial systems and mimic real customers, undertake time-consuming transactions on their behalf that result in a profit causing financial setbacks to the organizations and customers. Organizations will need to pay attention as a result of this. Its brand value is also affected. Organizations have learned from their mistakes. To prevent fraud and keep ahead of the criminals, it is necessary to maintain a constant focus. It's critical to keep an eye on major trends. We might be able to tell the difference between a legitimate and a fraudulent transaction, obtaining customer data such as geolocation, authentication, and so on, it is possible to keep track of the device's IP address during the session. Machine Learning (ML) will assume a significant part in the future in identifying examples of such frauds consequently. We use algorithms like decision trees, XGBoost, K-NN and others to find an optimal solution for our concerning project. © 2023 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Assessing Student Visual Fatigue in Virtual Semiconductor Labs via Head-Mounted Displays: A computer Vision Syndrome Questionnaire (CVS-Q) 3

Assessing Student Visual Fatigue in Virtual Semiconductor La...

引用

3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2023

作者： Alnagrat, Ahmed Jamah Ahmed Ismail, Rizalafande Che Akeel, Abubaker Almintisir Abubaker Salem, Asma Almkhtar Miftah Alhaj Khalefah, Salah Eldeen Ali Saad Idrus, Syed Zulkarnain Syed Department of Communication Department of Computer Science and Information Technology Perlis Kangar01000 Malaysia Wadi al-Shati Fezzan Libya Arau02600 Malaysia Wadi Alshatti University Faculty of Education Department of Mathematics and Computer Fezzan Libya Higher Institute of Sciences and Technology Department of Computer Science and Information Technology Tripoli Libya Higher Institute of Science and Technology Department of Computer Science and Information Technology Fezzan Libya Department of Communication Perlis Kangar01000 Malaysia

ISBN: (纸本)9798350319897

This paper evaluates visual fatigue among students in a virtual semiconductor lab using HMDs - the HP Reverb G2 and Oculus Quest 2 - and the CVS-Q questionnaire. The study measures the frequency of visual fatigue symptoms (never, occasionally, or always) and aims to determine the effects of HMD usage on visual fatigue and eye strain, providing insight into the benefits and drawbacks of using HMDs in virtual labs. The study was conducted during the COVID-19 pandemic and aims to determine the effects of HMD usage on visual fatigue and eye strain among students in a virtual semiconductor laboratory learning environment. The results of this evaluation will provide insight into the potential benefits and drawbacks of HMD usage in virtual laboratory environments and inform the development of strategies to mitigate visual fatigue. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Fog and Edge Computing-Based Smart Health Care System Using Machine Learning 7th

Fog and Edge Computing-Based Smart Health Care System Using ...

引用

7th International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2022

作者： Tripathy, Subhranshu Sekhar Tripathy, Niva Rath, Mamata Hu, Yu-Chen Pattanaik, Swarupa Samantaray, Swarnakanti Department of Computer Science and Engineering DRIEMS Autonomous College Odisha Cuttack India Department of Computer Science and Information Management Providence University Taichung City Taiwan GIET Khurdha Odisha Baniatangi India Nalanda Institute of Technology Odisha Bhubaneswar India School of Computer Engineering KIIT Deemed to be University Bhubaneswar India Department of Computer Science and Engineering SOET Centurion University of Technology and Management Bhubaneswar India

ISBN: (纸本)9789819950140

Data in the medical field include varying degrees of ambiguity and imprecision, which makes it difficult for doctors to improve the health of patients with a group of related suggestive disorders. As a result, doctors use data stored in networks and computing systems to identify a variety of illnesses in patients. The proposed strategy boosts the system’s effectiveness and makes accurate diagnoses and suggestions for treating life-threatening diseases easier. The adaptive prediction systems are assessed, and a machine learning-based model for heart disease detection is trained and compared to the relevant traditional approaches. When compared to other sophisticated classification methods, the cloud-fog-fog architecture was shown to be the most accurate. As a result, the suggested strategy is more accurate in identifying different cardiac issues and suggesting effective treatment options. The performance of the proposed system warrants its application in automated cardiac patient diagnostic and recommendation systems. The Heart Failure Clinical Records repository at UCI provided the dataset for this study, which has 13 characteristics. The experimental findings showed that the CNN model performs better than other deep learning and machine learning models which are proposed by eminent researchers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Secure UPI: Machine Learning-Driven Fraud Detection System for UPI Transactions 2

Secure UPI: Machine Learning-Driven Fraud Detection System f...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Rani, Rupa Alam, Adnan Javed, Abdul Ajay Kumar Garg Engineering College Ghaziabad Department of Computer Science & Engineering U.P. Ghaziabad India Banasthali Vidyapith Department of Computer Science & Engineering Rajasthan India Abes Institute of Technology Department of Computer Science & Engineering-Data Science U.P. Ghaziabad India

ISBN: (纸本)9798350371055

Secure UPI specializes in developing an advanced fraud detection gadget the usage of the effective XGBoost device getting to know set of rules to create an advanced fraud identity device. XGBoost is a properly-proper alternative for enhancing the precision of fraud detection fashions because of its reputation for dealing with tricky datasets with efficiency and its music record of success throughout multiple industries. In order to extract pertinent records, like transaction quantity, frequency, and place, our approach preprocesses UPI transaction facts. This article makes use of a labelled dataset to train the XGBoost version in order that we may also take gain of its sturdy prediction talents and capacity to handle imbalanced datasets. To help create a system that is less difficult to apprehend and use, feature importance evaluation is used to discover essential symptoms of feasible fraud. After training, the model is covered right into a real-time UPI transaction tracking device, in which it maintains an eye fixed out for any suspicious traits in incoming transactions. In order to lessen the results of fraudulent activity, the system is constructed with 98.2 % accuracy to send out instant notifications and take preventive steps. This challenge allows in improving UPI transaction security and advancing economic era are accomplished through demonstrating the performance of machine learning in fraud detection. © 2024 IEEE.

关键词： Dimensionality Reduction Fraud Detection Imbalanced Datasets Machine Learning PCA SMOTE UPI XGBoost

来源：评论

学校读者我要写书评

暂无评论

Secure transmission of colored images using a sparse matrix-based compression-then-encryption technique 5

Secure transmission of colored images using a sparse matrix-...

引用

5th IEEE International Conference on Recent Trends in computer science and technology, ICRTCST 2024

作者： Bose, Sayantan Biswas, Satarupa Hazra, Joydev Heritage Institute of Technology Department of Computer Science and Business Systems Kolkata India Heritage Institute of Technology Department of Information Technology Kolkata India

ISBN: (纸本)9798350351378

In the realm of modern communication, the transmission of substantial data, predominantly in the form of images, necessitates a delicate balance between data capacity optimization and ensuring secure transmission. This paper addresses this challenge through the introduction of a novel Compression-then-Encryption (CtE) scheme. The scheme incorporates a tailored luminance quantization matrix, optimizing luminance preservation, and employs sparse matrices to efficiently compress chrominance components. To fortify the security of image transmission, the CtE scheme integrates the standard AES-256 encryption algorithm. Through a synergistic approach, this scheme aims to enhance compression efficiency in the context of contemporary communication channels. © 2024 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Enhancing Gesture-Controlled Virtual Mouse and Virtual Keyboard Using AI Techniques

引用

Journal of Mobile Multimedia 2024年第2期20卷 473-494页

作者： Kotti, Jayasri Padmaja, B. Deepa, D. Department of Information Technology GMR Institute of Technology Andhra Pradesh Rajam India School of Computer Science and Engineering Vellore Institute of Technology Tamilnadu Vellore India

Artificial Intelligence has become an essential part of modern technology. Although computer technology is advanced, it can still be improved to make it more user-friendly. One way to do this is to replace touchscreen desktops with a virtual mouse and keyboard. This can reduce the need for gadgets and enhance human-computer interaction. During the COVID-19 pandemic, reducing human intervention and dependency on devices has been critical in controlling the spread of the virus. This is where a battery-powered or Bluetooth mouse, powered by virtual reality technology, can be helpful. The virtual mouse is created using OpenCV and virtual reality technology, with the proposed system utilizing advanced tools such as MediaPipe and Python. The MediaPipe library is particularly useful in artificial intelligence projects, as it enhances the efficiency of the model. The system is an AI-based mouse and keyboard that can be controlled using hand gestures. The user interacts with the system through the camera output displayed on the screen, while the webcam serves as an input device. Python and OpenCV tools are used for implementation, making it applicable in pandemic situations and smart teaching systems. The proposed system works on Enhancing gesture Controlled Virtual Mouse and Virtual Keyboard through Virtual Assistant using AI Techniques. © 2024 River Publishers.

关键词： Hand gestures media pipe OpenCV virtual assistant virtual keyboard virtual mouse

来源：评论

学校读者我要写书评

暂无评论

Vehicle Detection on Express Roads Using YOLOv7 with Taguchi Parameter Optimization Method

引用

Sensors and Materials 2024年第4期36卷 1605-1625页

作者： Chen, Mei-Kuei Chang, Chun-Lung Lin, Cheng-Jian Chen, Wen-Jong Department of Industrial Education and Technology National Changhua University of Education Changhua County50007 Taiwan Department of Artificial Intelligence and Computer Engineering National Chin-Yi University of Technology Taichung City41170 Taiwan Department of Computer Science & Information Engineering National Chin-Yi University of Technology Taichung City41170 Taiwan

In road traffic management, high-speed vehicle detection is often affected by factors such as vehicle speed, weather, camera angle, and image resolution, making vehicle detection on express roads very challenging, Therefore, we propose a Taguchi-based You Only Look Once (YOLOv7) model, called T-YOLOv7, for vehicle detection on high-speed roads. The Taguchi method is used to optimize the combination of hyperparameters of YOLOv7. Experimental results show the precision rate, recall rate, and F1-score of the proposed T-YOLOv7 to be 82.2, 86.3, and 84.2%, respectively. Compared with the original YOLOv7, T-YOLOv7 has improved precision, recall, and F1-score by 12.1, 17.9, and 15.0 percentage points, respectively. Compared with YOLOv4, the improvements in precision, recall, and F1-score using T-YOLOv7 are 4.0, 2.4, and 3.3 percentage points, respectively. The experimental results also show that the proposed T-YOLOv7 is effective in adjusting hyperparameters through the Taguchi method and can be applied to real-time vehicle detection in real environments. © MYU K.K.

关键词： Taguchi methods

来源：评论

学校读者我要写书评

暂无评论

Amalgamation of Transfer Learning and Explainable AI for Internet of Medical Things

引用

Recent Advances in computer science and Communications 2024年第4期17卷 40-53页

作者： Murugan, Ramalingam Paliwal, Manish Patibandla, Rama Seetha Maha Lakshmi Shah, Pooja Balaga, Tarakeswara Rao Gurrammagari, Deepti Raj Singaravelu, Parvathavarthini Yenduri, Gokul Jhaveri, Rutvij School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar India AP India Kallam Haranadhareddy Institute of Technology Andra Pradesh Guntur India Department of Computer Applications Kongu Engineering College Erode Perundurai India

The Internet of Medical Things (IoMT), a growing field, involves the interconnection of medical devices and data sources. It connects smart devices with data and optimizes patient data with real time insights and personalized solutions. It is mandatory to hold the development of IoMT and join the evolution of healthcare. This integration of Transfer Learning and Explainable AI for IoMT is considered to be an essential advancement in healthcare. By making use of knowledge transfer between medical domains, Transfer Learning enhances diagnostic accuracy while reducing data necessities. This makes IoMT applications more efficient which is considered to be a mandate in today’s healthcare. In addition, explainable AI techniques offer transparency and interpretability to AI driven medical decisions. This can foster trust among healthcare professionals and patients. This integration empowers personalized medicine, supports clinical decision making, and confirms the responsible handling of sensitive patient data. Therefore, this integration promises to revolutionize healthcare by merging the strengths of AI driven insights with the requirement for understandable, trustworthy, and adaptable systems in the IoMT ecosystem. © 2024 Bentham science Publishers.

关键词： Knowledge management

来源：评论

学校读者我要写书评

暂无评论

Efficient Implementation of Aperture Fill Time Correction for Wideband Array Using the Low-complexity Keystone Transform

引用

Progress In Electromagnetics Research C 2023年 136卷 101-112页

作者： Wang, Lin Jiang, Yiyang Jiang, Yu Tian, Baoli Shen, Mingwei College of Computer and Information Engineering Hohai University Nanjing China Unit 95438 of PLA Air Force Meishan China Science and Technology on Electronic Information Control Laboratory Chengdu China

In order to remove the influence of the aperture fill time (AFT) for wideband array, the scaling principle of the Keystone (KT) transform is applied to eliminate the linear coupling between spatial domain and frequency domain of wideband array signal. However, the classic KT transform is implemented by interpolation Sinc which is difficult to apply in engineering and leads to the serious problem of insufficient data. To address this, a realization of the low-complexity KT transform is presented, and it is implemented using only the Chirp-z transform (CZT) and fast Fourier transforms (FFT). Additionally, an Autoregressive (AR) model is proposed to compensate the insufficient data for each range, and the order of AR is estimated by the rank of the signal covariance matrix. Simulation results demonstrate that the proposed algorithm significantly reduces computational burden and improves the performance of wideband array beamforming. © 2023, Electromagnetics Academy. All rights reserved.

关键词： Fast Fourier transforms

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：