检索结果-内蒙古大学图书馆

Crops Leaf Diseases Recognition:A Framework of Optimum Deep Learning Features

computers, Materials & Continua 2023年第1期74卷 1139-1159页

作者： Shafaq Abbas Muhammad Attique Khan Majed Alhaisoni Usman Tariq Ammar Armghan Fayadh Alenezi Arnab Majumdar Orawit Thinnukool Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj11942Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakakahSaudi Arabia Faculty of Engineering Imperial College LondonLondonSW72AZUK College of Arts Mediaand TechnologyChiang Mai UniversityChiang Mai50200Thailand

Manual diagnosis of crops diseases is not an easy process;thus,a computerized method is widely *** couple of years,advancements in the domain ofmachine learning,such as deep learning,have shown substantial ***,they still faced some challenges such as similarity in disease symptoms and irrelevant features *** this article,we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases *** proposed architecture consists of five *** the first step,data augmentation is performed to increase the numbers of training *** the second step,pre-trained DarkNet19 deep model is opted and fine-tuned that later utilized for the training of fine-tuned model through transfer *** features are extracted from the global pooling layer in the next step that is refined using Improved Cuckoo search *** best selected features are finally classified using machine learning classifiers such as SVM,and named a few more for final classification *** proposed architecture is tested using publicly available datasets–Cucumber National Dataset and Plant *** proposed architecture achieved an accuracy of 100.0%,92.9%,and 99.2%,*** with recent techniques is also performed,revealing that the proposed method achieved improved accuracy while consuming less computational time.

关键词： Crops diseases preprocessing convolutional neural network features optimization machine learning

来源：评论

学校读者我要写书评

暂无评论

Intelligent Real-Time Hypoglycemia Prediction for Type 1 Diabetes 2

Intelligent Real-Time Hypoglycemia Prediction for Type 1 Dia...

引用

2nd International Conference of Intelligent Methods, Systems and Applications, IMSA 2024

作者： Mahdy, Nevien A. Elnokrashy, Ahmed F. Hammad, D.A. Mohamed, Wael A. Benha University Benha Faculty of Engineering Electrical Engineering Department Benha Egypt Nile University Faculty of Information Technology and Computer Science Computer Science Department Giza Egypt Benha University Benha Faculty of Engineering Basic Engineering Sciences Department Benha Egypt

ISBN: (纸本)9798350362633

Hypoglycemia in Type 1 Diabetes (T1D) refers to a condition where blood glucose (BG) levels drop to abnormally low levels, typically below 70 mg/dL. This can occur when there is an excessive amount of insulin relative to the blood glucose level, leading to an imbalance that can be dangerous and potentially life-threatening if not promptly treated. The availability of large amounts of data from continuous glucose monitoring (CGM), insulin doses, carbohydrate intake, and additional vital signs, together with deep learning (DL) techniques, has revolutionized algorithmic approaches for BG prediction in T1D, achieving superior performance. In our study, we employed a Long Short-Term Memory (LSTM) neural network architecture to predict hypoglycemia events in patients with T1D. For the training and testing, we utilized the OhioT1DM (2018) dataset. In addition, real-time data collected from an individual patient for the evaluation. This patient utilized the CGM FreeStyle Libre (FSL) system, along with a smartwatch to monitor step count. The LSTM model exhibited performance demonstrating exceptional levels of sensitivity, specificity, and accuracy scores of 97.09%, 94.17%, and 95.63%, respectively, when assessed using the Ohio test dataset. Our research provides strong evidence supporting the system's efficacy in managing hypoglycemia events in individuals diagnosed with T1D. © 2024 IEEE.

关键词： Classification Deep learning Glucose prediction Hypoglycemia Type 1 diabetes

来源：评论

学校读者我要写书评

暂无评论

Proposed 3D chaos-based medical image cryptosystem for secure cloud-IoMT eHealth communication services

引用

Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 1-28页

作者： El-Shafai, Walid Khallaf, Fatma El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Ahram Canadian University Giza 6th October City Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh84428 Saudi Arabia

Medical image encryption is a mandatory process in various healthcare, Internet of Medical Things (IoMT) and cloud services. This paper provides a robust cryptosystem based on a 3D chaotic map for the medical image encryption in secure IoMT and cloud services. The proposed encryption method depends on a 3D chaotic map. With this map, a nonlinear ciphering process is implemented for pixel value diffusion and position permutation. Five operations are conducted in the suggested cryptosystem on the medical images to be transmitted in order to attain a high security level. These operations are 3D chaos generation, chaos histogram equalization, row rotation, column rotation, and XOR operation. To validate the suggested cryptosystem, different medical images with different characteristics are tested. Moreover, the suggested cryptosystem and more recent state-of-the-art security systems are discussed and analyzed in a comparative study. Different assessment parameters are adopted to assess the suggested cryptosystem, which reveals high security performance. The simulation outcomes show that the suggested cryptosystem is trustworthy. Furthermore, it offers high robustness levels and recommended security levels for utilization in healthcare, IoMT and cloud service applications. It is observed that the amount of average entropy obtained by the proposed 3D chaos cryptosystem is 7.95 which is very close to its best value of 8, and the average NPCR value is 99.62% which is also much close to its supreme value of 99.60%. In addition, all other results scored for the test evaluation parameters on the suggested cryptosystem are superior to those of the traditional security systems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

DCCMamba: A Dual-stream Cross-time and Cross-feature with Mamba for Multivariate Time Series Forecasting

DCCMamba: A Dual-stream Cross-time and Cross-feature with Ma...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Liang, Senlin Wang, Zhuoyue Zhao, Chunna Huang, Yaqun Xu, Jinpeng Yang, Yaoyuan School of Information Science & Engineering Yunnan University Kunming China Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley United States

ISBN: (纸本)9798350368741

In recent years, multivariate time series forecasting (MTSF) has gained significant attention. And transformer-based models have showed strong performance. However, the quadratic complexity of attention mechanisms leads to inefficiency and high overhead. The Mamba state-space model offers a more efficient alternative with lower complexity and fewer parameters. However, its unilateral nature limits the effective capture of time and feature dimensions. To address this, we propose A Dual-stream Cross-time and Cross-feature with Mamba (DCCMamba) for MTSF. Specifically, we employ a dual-stream structure to extract different information from the time and feature dimensions. One stream encodes data from a feature perspective and passes it through a Mamba layer to capture cross-time information. The other stream encodes the data from the time perspective, decomposes it into trend and seasonal components, and captures cross-feature information using a Mamba layer. Finally, we fuse the cross-feature information and cross-time information to get the final result. Experiments on four public datasets demonstrate that DCCMamba achieves state-of-the-art performance. © 2025 IEEE.

关键词： Cross-feature Cross-time dual-stream Mamba time series

来源：评论

学校读者我要写书评

暂无评论

Full-Distance Evasion of Pedestrian Detectors in the Physical World 38

Full-Distance Evasion of Pedestrian Detectors in the Physica...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Cheng, Zhi Hu, Zhanhao Liu, Yuqiu Li, Jianmin Su, Hang Hu, Xiaolin Department of Computer Science and Technology Tsinghua University Beijing China Department of Electrical Engineering and Computer Sciences UC Berkeley United States Department of Technology Beijing Forestry University Beijing China

Many studies have proposed attack methods to generate adversarial patterns for evading pedestrian detection, alarming the computer vision community about the need for more attention to the robustness of detectors. However, adversarial patterns optimized by these methods commonly have limited performance at medium to long distances in the physical world. To overcome this limitation, we identify two main challenges. First, in existing methods, there is commonly an appearance gap between simulated distant adversarial patterns and their physical world counterparts, leading to incorrect optimization. Second, there exists a conflict between adversarial losses at different distances, which causes difficulties in optimization. To overcome these challenges, we introduce a Full Distance Attack (FDA) method. Our physical world experiments demonstrate the effectiveness of our FDA patterns across various detection models like YOLOv5, Deformable-DETR, and Mask RCNN. Codes available at https://***/zhicheng2T0/***. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Review of Techniques for Integrating Security in Software Development Lifecycle

引用

computers, Materials & Continua 2025年第1期82卷 139-172页

作者： Hassan Saeed Imran Shafi Jamil Ahmad Adnan Ahmed Khan Tahir Khurshaid Imran Ashraf College of Electrical and Mechanical Engineering National University of Sciences and Technology(NUST)Rawalpindi46604Pakistan Department of Computer Science Abasyn University Islamabad CampusIslamabad45510Pakistan Military College of Signals National University of Sciences and Technology(NUST)Rawalpindi46600Pakistan Department of Electrical Engineering Yeungnam UniversityGyeongsan38541Republic of Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Republic of Korea

Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our *** conduct research in this field,periodic comparative analysis is needed with the new techniques coming up *** purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle(SDLC)by analyzing the articles published in the last two decades and to propose a way *** review follows Kitchenham’s review *** review has been divided into three main stages including planning,execution,and *** the selected 100 articles,it becomes evident that need of a collaborative approach is necessary for addressing critical software security risks(CSSRs)through effective risk management/estimation *** risks using a numeric scale enables a comprehensive understanding of their severity,facilitating focused resource allocation and mitigation *** a comprehensive understanding of potential vulnerabilities and proactive mitigation efforts facilitated by protection poker,organizations can prioritize resources effectively to ensure the successful outcome of projects and initiatives in today’s dynamic threat *** review reveals that threat analysis and security testing are needed to develop automated tools for the *** estimation of effort required to prioritize potential security risks is a big challenge in software *** accuracy of effort estimation can be further improved by exploring new techniques,particularly those involving deep *** is also imperative to validate these effort estimation methods to ensure all potential security threats are *** challenge is selecting the right model for each specific security *** achieve a comprehensive evaluation,researchers should use well-known benchmark checklists.

关键词： Software development lifecycle systematic literature review critical software security risks national institute of standards and technology DevSecOps open web application security project McGraw’s touch points

来源：评论

学校读者我要写书评

暂无评论

Video and image quality improvement using an enhanced optimized dehazing technique

引用

Multimedia Tools and Applications 2024年 1-19页

作者： Ayoub, Abeer El-Shafai, Walid El-Samie, Fathi E. Abd Hamad, Ehab K. I. EL-Rabaie, El-Sayed M. Electrical Engineering Department Faculty of Engineering Aswan University Aswan81542 Egypt Department of Electronics and Electrical Communication Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

The detrimental effects of atmospheric haze frequently plague outdoor imagery. This phenomenon arises from the scattering of light by minute particles within the ambient environment surrounding the scene to be imaged. Haze engenders an overall whitening of the image, leading to diminished contrast. To address these issues and enhance the quality of hazy images and videos, an enhanced dehazing technique is proposed. The proposed technique includes image enhancement before the optimal dehazing process. The enhancement stage entails the implementation of both homomorphic processing and Contrast Limited Adaptive Histogram Equalization (CLAHE), serving to control the image dynamic range, while concurrently heightening the image contrast. The culminating stage encompasses an optimized dehazing technique, adept at expunging haze-induced artifacts from images. The homomorphic processing and CLAHE, applied in the pre-processing step, establish a foundation for the subsequent dehazing procedure. This proposed methodology is systematically applied to a gamut of visual outputs, including visible videos, Near-Infrared (NIR) frames, and authentic hazy images. Comparative evaluations of the proposed technique, homomorphic-processing-based enhanced dehazing, and standalone dehazing techniques is undertaken on different video types encompassing five frames. It is evident that the proposed technique, synergizing the homomorphic processing, CLAHE, and dehazing, outperforms alternative strategies. Furthermore, the proposed technique is subjected to a comparative study with various existing dehazing techniques over real hazy images. The assessment depends on Peak Signal-to-Noise Ratio (PSNR), correlation, and entropy metrics. The results underscore the efficacy of the proposed technique, particularly in terms of spectral entropy enhancement of dehazed frames. For both visible and NIR frames, the percentages of enhancement by the proposed technique are 17.66% and 118.48%, respectively. ©

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

FPGA Hardware Trojan Detection: Golden-Free Machine Learning Approach

FPGA Hardware Trojan Detection: Golden-Free Machine Learning...

引用

2023 IEEE National Aerospace and Electronics Conference, NAECON 2023

作者： Ghimire, Ashutosh Amsaad, Fathi Hossain, Tanvir Hoque, Tamzidul Sherif, Ahmed Wright State University Department of Computer Science and Engineering United States University of Kansas Department of Electrical Engineering and Computer Science United States School of Computing Sciences and Computer Engineering The University of Southern Mississippi United States

ISBN: (纸本)9798350338782

Ensuring trust in the semiconductor IC supply chain necessitates the critical detection of Hardware Trojans, yet current methods relying on side-channel analysis often require the use of golden chips for verification. This research paper presents a novel approach to detect Hardware Trojans in the semiconductor IC supply chain, addressing the need for trust and eliminating the use of golden chips. By combining unsuper-vised machine learning and side-channel analysis, the proposed technique leverages unique features from on-chip ring-oscillator networks to identify anomalies through unsupervised clustering. Evaluation on FPGA chips with Trojan insertion demonstrated exceptional accuracy, surpassing alternative methods with a 99 % accuracy rate. The centroid-based clustering model exhibited superior performance with a slight edge in false positive rate and an fl score. This research contributes to enhancing trust in semiconductor IC supply chains by offering a fresh perspective on Hardware Trojan detection. © 2023 IEEE.

关键词： Hardware security

来源：评论

学校读者我要写书评

暂无评论

Ultra-low-defect homoepitaxial micro-LEDs with enhanced efficiency and monochromaticity for high-PPI AR/MR displays

引用

PhotoniX 2024年第1期5卷 335-356页

作者： Yibo Liu Guobin Wang Feng Feng Mengyuan Zhanghu Zhengnan Yuan Zichun Li Ke Xu Hoi Sing Kwok Zhaojun Liu Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong Kong SARChina Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of SciencesJiangsu Institute of Advanced SemiconductorsSuzhouChina

The issue of brightness in strong ambient light conditions is one of the critical obstacles restricting the application of augmented reality(AR)and mixed reality(MR).Gallium nitride(GaN)-based micro-LEDs,renowned for their exceptional brightness and stability,are considered the foremost contenders for AR ***,conventional heteroepitaxial growth micro-LED devices confront formidable challenges,including substantial wavelength shifts and efficiency *** this paper,we firstly demonstrated the high-quality homoepitaxial GaN-on-GaN micro-LEDs microdisplay,and thoroughly analyzed the possible benefits for free-standing GaN substrate from the material-level characterization to device optoelectronic properties and microdisplay application compared with sapphire *** GaN-on-GaN structure exhibits a superior crystal quality with ultra-low threading dislocation densities(TDDs)of~105 cm^(-2),which is three orders of magnitude lower than that of *** an in-depth size-dependent optoelectronic analysis of blue/green emission GaN-on-GaN/Sapphire micro-LEDs from 100×100 shrink to 3×3μm^2),real that a lower forward voltage and series resistance,a consistent emission wavelength(1.21 nm for blue and 4.79 nm for green@500 A/cm2),coupled with a notable reduction in efficiency droop ratios(15.6%for blue and 28.5%for green@500 A/cm^(2))and expanded color gamut(103.57%over Rec.2020)within GaN-on-GaN 10μm *** but not least,the GaN-on-GaN micro-display with 3000 pixels per inch(PPI)showcased enhanced display uniformity and higher luminance in comparison to its GaN-on-Sapphire counterpart,demonstrating significant potentials for high-brightness AR/MR applications under strong ambient light.

关键词： optoelectronic ambient epitaxial

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Identification Using Data Augmentation and Transfer Learning Approach

引用

computer Systems science & engineering 2023年第8期46卷 1845-1861页

作者： K.Kavin Kumar P.M.Dinesh P.Rayavel L.Vijayaraja R.Dhanasekar Rupa Kesavan Kannadasan Raju Arfat Ahmad Khan Chitapong Wechtaisong Mohd Anul Haq Zamil S.Alzamil Ahmed Alhussen Department of Electronics and Communication Engineering Kongu Engineering College638060Tamil NaduIndia Department of Electronics and Communication Engineering Sona College of Technology636005Tamil NaduIndia Department of Computer Science and Engineering Sri Sairam Institute of TechnologyChennai600044Tamil NaduIndia Department of Electrical and Electronics Engineering Sri Sairam Institute of TechnologyChennai600044Tamil NaduIndia Department of Computer Science and Engineering Sri Venkateswara College of EngineeringSriperumbudur602117Tamil NaduIndia Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117Tamil NaduIndia Department of Computer Science College of ComputingKhon Kaen UniversityKhonKaen40002Thailand School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

A brain tumor is a lethal neurological disease that affects the average performance of the brain and can be *** India,around 15 million cases are diagnosed *** mitigate the seriousness of the tumor it is essential to diagnose at the ***,the manual evaluation process utilizing Magnetic Resonance Imaging(MRI)causes a few worries,remarkably inefficient and inaccurate brain tumor ***,the examination process of brain tumors is intricate as they display high unbalance in nature like shape,size,appearance,and ***,a precise and expeditious prognosis of brain tumors is essential for implementing the of an implicit *** computer models adapted to diagnose the tumor,but the accuracy of the model needs to be *** all the above mentioned things,this work aims to identify the best classification system by considering the prediction accuracy out of Alex-Net,ResNet 50,and Inception *** augmentation is performed on the database and fed into the three convolutions neural network(CNN)models.A comparison line is drawn between the three models based on accuracy and *** accuracy of 96.2%is obtained for AlexNet with augmentation and performed better than ResNet 50 and Inception V3 for the 120th *** the suggested model with higher accuracy,it is highly reliable if brain tumors are diagnosed with available datasets.

关键词： AlexNet brain tumor data augmentation inception V3 ResNet 50

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：