检索结果-内蒙古大学图书馆

26th International Workshop on Mobile Computing Systems and Applications, HOTMOBILE 2025

作者： Huang, Runxi Ouyang, Xiaomin Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9798400714030

Achieving real-time multimodal inference on devices is crucial for time-critical and privacy-sensitive applications. Existing methods primarily focus on optimizing the latency of model inference while neglecting the data collection process. We introduce MMEdge, an on-device, end-to-end multimodal inference framework. MMEdge employs a cross-modality speculative sensing and encoding approach to enhance inference efficiency and robustness at runtime. © 2025 Copyright held by the owner/author(s).

关键词： Edge computing

来源：评论

学校读者我要写书评

暂无评论

Detection of Caries and Hypodontia using Deep Learning and Explainable AI 18

Detection of Caries and Hypodontia using Deep Learning and E...

引用

18th International Conference on Open Source Systems and Technologies, ICOSST 2024

作者： Kamran, Muhammad Waseem, Muhammad Shafi, Numan Zahid, Abdullah University of Engineering and Technology Department of Computer Science Lahore Pakistan

ISBN: (纸本)9798331508692

In today's world of technology breakthroughs, incorporating cutting-edge procedures has become essential, especially in healthcare, where an early and precise diagnosis is critical for improving patient outcomes and saving lives. Dental caries is an infectious bacterial disease primarily caused by the interaction of oral bacteria with dietary sugars, leading to plaque formation on teeth. Millions of people worldwide are facing this disease. Hypodontia is another dental term that healthcare providers use to describe congenitally missing teeth. We employed an AI-driven healthcare solution by utilizing a transformer-based image classification model, Vision Transformer (VIT), for the detection of dental caries and hypodontia. A dataset containing both periapical and panoramic dental x-rays utilized to gain maximum insights into teeth. The dataset was divided into 60% for training, 20% for testing, and 20% for validation. Data augmentation techniques are applied to enhance the diversity of training data and mitigate overfitting. The proposed model demonstrated remarkable performance and achieved an accuracy of 96.63% with evaluation matrices Precision, Recall, and F1-score of 96.60, 96.63, and 96.57 % respectively. Unlike Convolutional Neural Networks (CNN) which are black boxes, we utilized the Explainable Artificial Intelligence (XAI) models such as LIME, SHAP, and GRAD-CAM to gain insights into the inner workings of the VIT model. The XAI models contributed to fostering trust among medical dentists and medical professionals. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning and Nature Inspired Algorithm Based Hybrid Approach for Detection of IoT Attacks 4

A Machine Learning and Nature Inspired Algorithm Based Hybri...

引用

4th International Conference on computer, Communication, Control and Information technology, C3IT 2024

作者： Sikdar, Subinoy Kule, Malay Indian Institute of Engineering Science and Technology Department of Computer Science and Technology Howrah Shibpur India

ISBN: (纸本)9798350389128

Internet of Things (IoT) is revolutionizing our daily life, shifting manual systems to computerized ones. With the proliferation of IoT devices connected via the internet, ensuring security against malicious attacks is critical. So, the security of information is the greatest concern in modern days as the IoT devices are attacked by various malicious services. In this paper, we have proposed a hybrid attack detection method using machine learning and nature inspired algorithm. The main objective of this paper is to find out the best feature(s) as well as the best algorithms, which detect the attack accurately. We have used CICIoT2023 dataset to classify the malicious attacks and benign traffic. Decision Tree and One Rule algorithm has been applied on the dataset and both the algorithms reached the accuracy up to 98.22% and 98.99% respectively. An ensemble learning method was also developed using Random Forest algorithm. Furthermore, a hybrid attack detection approach has been implemented using Decision Tree and Cuckoo Search Algorithm, which can perform better than Random Forest model. The hybrid classifier has obtained the accuracy up to 99.40%, whereas the Random Forest model reached the accuracy up to 99.28%. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Constrained Evolutionary Multi-objective Optimization Algorithms on Artificial and Real-World Problems 1

引用

13th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2025

作者： Nan, Yang Ishibuchi, Hisao Pang, Lie Meng Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (数字)9789819635382

ISBN: (纸本)9789819635375

Most real-world optimization problems have multiple objectives and constraints. To address constrained multi-objective optimization problems (CMOPs), researchers have proposed many constrained evolutionary multi-objective optimization (EMO) algorithms. They usually evaluate the proposed constrained EMO algorithms on artificial CMOPs in the literature. As a result, some newly specialized constrained EMO algorithms are designed for those artificial problems. Our previous work demonstrated that an old EMO algorithm NSGA-II with a simple constraint handling mechanism can outperform some newly proposed algorithms on real-world CMOPs. In this paper, we further examine the performance of constrained EMO algorithms on artificial and real-world CMOPs. We also analyze the relationship between algorithms’ performance and problems’ properties. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Monolithic full-color active-matrix micro-LED microdisplay using InGaN/AlGaInP heterogeneous integration

引用

Light(science & Applications) 2023年第11期12卷 2459-2467页

作者： Longheng Qi Peian Li Xu Zhang Ka Ming Wong Kei May Lau Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina

A prototype of full-color active-matrix micro-light-emitting diode(micro-LED)micro-display with a pixel density of 391 pixel per inch(ppi)using InGaN/AlGaInP heterogeneous integration is *** blue/green dual-color micro-LED arrays realized on a single metal organic chemical vapor deposition(MOCVD)-grown GaN-on-Si epiwafer and AlGaInP red micro-LED arrays are both monolithically fabricated,followed by the integration with a common complementary metal oxide semiconductor(CMOS)backplane via flip-chip bonding technology to form a doublelayer thin-film display ***-color images with decent color gamut and brightness are successfully displayed through the fine adjustment of driving current densities of RGB *** full-color display combines the advantages of high quantum efficiency of InGaN material on blue/green light and AlGaInP material on red light through heterogeneous integration and high pixel density through monolithic fabrication approach,demonstrating the feasibility and prospects of high brightness,good color performance,and high-resolution micro-LED microdisplays in future metaverse applications.

关键词： AlGaInP integration matrix

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Based Air Pollution Monitoring and Forecasting

Machine Learning-Based Air Pollution Monitoring and Forecast...

引用

International Conference on Machine Learning and Big Data Analytics, ICMLBDA 2023

作者： M, Naga Ravindra Babu Durga Satish, M. Prasanthi, B.V. Jagadeesh, S.V.V.D. Janardhana Naidu, J.N.S.S. Pradeep, Immidi Kali Department of Computer Science & Engineering Vishnu Institute of Technology Bhimavaram India

ISBN: (纸本)9783031513374

Today, the governments of developing countries are focusing more on air pollution. Air pollution occurs because of factors like fuel use in vehicles such as private transport, industries, and, more importantly, the burning of waste like plastic and grass. These are a few of the elements that contribute to air pollution. All of these factors have an impact on air quality. It can be calculated or determined by using PM2.5 and other variables. If this level is high, then it may be a serious problem for people’s health. To control air pollution, continuous pollution monitoring is required. Here, different machine learning models like linear regression, decision tree classifiers, random forest classifiers, and KNN classifiers are used to detect whether the sample of air is polluted or not. On the basis of previous readings of PM2.5, NH3, CO, NO, NOx, and NO2, SO2 is used to predict the future values of the AQI. By collecting datasets of the daily atmospheric conditions of a specific city or town, this system is able to predict the PM2.5 level and also detect the air pollution status. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Glaucoma Susceptibility Assessment and Lifestyle Guidance 5th

AI-Driven Glaucoma Susceptibility Assessment and Lifestyle G...

引用

5th EAI International Conference on Cognitive Computing and Cyber Physical Systems, IC4S 2024

作者： Talla, Ganesh Venkata Sundar Akhil, Toram Rajeev Thatikonda, Surendra potnuru, Tarun Lalitha, Chirravuri Surya Naga Sai Bonthu, Sridevi Department of Computer Science and Engineering Vishnu Institute of Technology Bhimavaram India

ISBN: (纸本)9783031770746

This project addresses the global health challenge posed by glaucoma through the development of an innovative Python-based application. Utilizing advanced machine learning techniques, specifically the VGG16 model with transfer learning, the application aims to enhance glaucoma diagnosis and management. By automating glaucoma severity classification into distinct categories, including No_DR, Proliferate_DR, Mild, Moderate, and Severe, the application provides personalized medical advice tailored to the predicted severity. The user-friendly interface, powered by the Tkinter library, enables individuals to upload eye images for real-time analysis, empowering them to actively monitor their eye health. Through early detection and informed decision-making, the application strives to slow down the progression of glaucoma and enhance overall quality of life. This project exemplifies the intersection of technology and healthcare, promising to positively impact lives by promoting early awareness and proactive glaucoma management. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Self-supervised few-shot medical image segmentation with spatial transformations

引用

Neural Computing and Applications 2024年第30期36卷 18675-18691页

作者： Titoriya, Ankit Kumar Singh, Maheshwari Prasad Singh, Amit Kumar Department of Computer Science & amp Engineering National Institute of Technology Patna Ashok Rajpath Bihar Patna800005 India

Deep learning-based segmentation models often struggle to achieve optimal performance when encountering new, unseen semantic classes. Their effectiveness hinges on vast amounts of annotated data and high computational resources for training. However, a promising solution to mitigate these challenges is the adoption of few-shot segmentation (FSS) networks, which can train models with reduced annotated data. The inherent complexity of medical images limits the applicability of FSS in medical imaging, despite its potential. Recent advancements in self-supervised label-efficient FSS models have demonstrated remarkable efficacy in medical image segmentation tasks. This paper presents a novel FSS architecture that enhances segmentation accuracy by utilising fewer features than existing methodologies. Additionally, this paper proposes a novel self-supervised learning approach that utilises supervoxel and augmented superpixel images to further enhance segmentation accuracy. This paper assesses the efficacy of the proposed model on two different datasets: abdominal magnetic resonance imaging (MRI) and cardiac MRI. The proposed model achieves a mean dice score and mean intersection over union of 81.62% and 70.38% for abdominal images, and 79.38% and 65.23% for cardiac images. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Enhancing Evidence Protection and Authenticity with Blockchain in the Judicial Sectors 3

Enhancing Evidence Protection and Authenticity with Blockcha...

引用

3rd International Conference on Disruptive Technologies, ICDT 2025

作者： Singh, Satyendra Singh, Laxman Yadav, Vijay Prakash Singh, Tilak Dubey, Yashodutt Abes Institute of Technology Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798331519582

The forensic evidence in the legal sector is now much more challenging to authenticate its integrity and authenticity. In fact, evidence management is easily tampered with, not authorized, and inconsistent because of the traditional systems that lack data integrity. This paper presents an end-to this challenge through the invention of using blockchain technology in evidence preservation and authentication. This paper presents a proposed system for providing an immutable and transparent chain of custody for forensic evidence using distributed ledger technologies and smart contracts. The methodology gives in detail a review of blockchain's ability to protect evidence from unauthorized access by other people as well as the ability of distributed ledgers to permit organizations to interoperate on the process of handling evidence. The results show that blockchain does not merely provide tamper-proof evidence custody but also provides an apparent and secure form of transferring custody, making judicial systems more reliable. Some of the challenges include scalability, security breaches, and regulatory compliance;nonetheless, blockchain is the revolutionary solution for enhancing forensic record storage and court documentation. This study throws the spotlight on blockchain's capability in revolutionizing the protection and authentication of evidence for criminal investigations in the future. © 2025 IEEE.

关键词： computer forensics

来源：评论

学校读者我要写书评

暂无评论

Utilizing Deep Learning for Detecting Malaria in Blood Cell Images

Utilizing Deep Learning for Detecting Malaria in Blood Cell ...

引用

2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Wahiduzzaman, Md. Fokir, Md. Jahid Rimi, Sadia Afrin Parvin, Tunazzina Hossain, Md Jakir Ahnaf Morshed, Md. Reza, Ahmed Wasif Arefin, Mohammad Shamsul East West University Department of Computer Science and Engineering Dhaka Bangladesh Chittagong University of Engineering and Technology Department of Computer Science and Engineering Chittagong Bangladesh

ISBN: (纸本)9798331529765

Plasmodium malaria, a disease transmitted by mosquitoes, has claimed the lives of more than 7.6 million individuals. The conventional methods for detecting this disease are laborious and pose diagnostic challenges. In this study, the performance of a convolutional neural network (CNN) employing transfer learning, specifically a CNN called ShuffleNet, was investigated for classifying infected and uninfected malaria parasite cells in thick blood smears. The dataset utilized in this research comprises 26,161 images categorized into infected and uninfected cells. In this study, the dataset comprises 26,161 images categorized into infected and uninfected cells, providing a comprehensive basis for analysis. The proposed method achieved remarkable results, with a training accuracy of 99.57% and a testing accuracy of 99.77%, indicating its strong performance across various datasets. These findings underscore the potential of deep learning approaches in enhancing malaria detection from blood cell images, offering promising avenues for further research and application in clinical settings. © 2024 IEEE.

关键词： Convolutional neural networks

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：