检索结果-南通市图书馆

Gastrointestinal Diseases Classification Using Deep Transfer Learning and Features Optimization

Computers, Materials & Continua 2023年第4期75卷 2227-2245页

作者： Mousa Alhajlah Muhammad Nouman Noor Muhammad Nazir awais mahmood Imran Ashraf Tehmina Karamat College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Engineering HITEC UniversityTaxila47080Pakistan Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan

Gastrointestinal diseases like ulcers, polyps’, and bleeding areincreasing rapidly in the world over the last decade. On average 0.7 millioncases are reported worldwide every year. The main cause of gastrointestinaldiseases is a Helicobacter Pylori (H. Pylori) bacterium that presents in morethan 50% of people around the globe. Many researchers have proposeddifferent methods for gastrointestinal disease using computer vision *** of them focused on the detection process and the rest of themperformed classification. The major challenges that they faced are the similarityof infected and healthy regions that misleads the correct classificationaccuracy. In this work, we proposed a technique based on Mask Recurrent-Convolutional Neural Network (R-CNN) and fine-tuned pre-trainedResNet-50 and ResNet-152 networks for feature extraction. Initially, the region ofinterest is detected using Mask R-CNN which is later utilized for the trainingof fine-tuned models through transfer learning. Features are extracted fromfine-tuned models that are later fused using a serial approach. Moreover, anImproved Ant Colony Optimization (ACO) algorithm has also opted for thebest feature selection from the fused feature vector. The best-selected featuresare finally classified using machine learning techniques. The experimentalprocess was conducted on the publicly available dataset and obtained animproved accuracy of 96.43%. In comparison with state-of-the-art techniques,it is observed that the proposed accuracy is improved.

关键词： Diseases deep learning endoscopy gastrointestinal tract transfer learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Hybrid Evolutionary Algorithm Based Relevance Feedback Approach for Image Retrieval

引用

Computers, Materials & Continua 2022年第1期70卷 963-979页

作者： awais mahmood Muhammad Imran Aun Irtaza Qammar Abbas Habib Dhahri Esam Mohammed Asem Othman Arif Jamal Malik Aaqif Afzaal Abbasi College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Shaheed Zulfikar Ali Bhutto Institute of Science and Technology(Islamabad Campus) 44000Pakistan University of Engineering and Technology Taxila Pakistan International Islamic University Islamabad44000Pakistan Faculty of Sciences and Technology University of KairouanSidi Bouzid4352Tunisia Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan

Searching images fromthe large image databases is one of the potential research areas of multimedia *** most challenging task for nay CBIR system is to capture the high level semantic of *** researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback(RF).However existing RF based approaches needs a number of iteration to fulfill user’s *** paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the *** previous research work it is reported that SVM based RF approach generating better results for ***,this paper focused on SVM based RF *** enhance the performance of SVM based RF approach this research work applied Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)before applying SVM on user *** main objective of using thesemeta-heuristic was to increase the positive image sample size from *** steps PSO is applied by incorporating the user feedback and secondly GA is applied on the result generated through PSO,finally SVM is applied using the positive sample generated through *** proposed technique is named as Particle Swarm Optimization Genetic Algorithm-Support Vector Machine Relevance Feedback(PSO-G A-SVMRF).Precisions,recall and F-score are used as performance metrics for the assessment and validation of PSO-GA-SVM-RF approach and experiments are conducted on coral image dataset having 10908 *** experimental results it is proved that PSO-GA-SVM-RF approach outperformed then various well known CBIR approaches.

关键词： Feature selection image retrieval particle swarm optimization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

引用

Computers, Materials & Continua 2022年第2期70卷 2761-2775页

作者： Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry awais mahmood Muhammad Attique Mohamed Habib Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Faculty of Engineering Port Said UniversityPort Fuad CityEgypt

In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting *** is why an automated weapon detection system is *** automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good ***,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection *** models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance *** research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key *** proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur *** proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 *** results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are *** reached 0.010 s per frame compared to the 0.17 s of the Faster *** is promising to be used in the field of security and weapon detection.

关键词： Video surveillance weapon detection you only look once convolutional neural networks

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

ExpressionHash: Securing Telecare Medical Information Systems Using BioHashing

引用

Computers, Materials & Continua 2021年第6期67卷 2747-2764页

作者： Ayesha Riaz Naveed Riaz awais mahmood Sajid Ali Khan Imran mahmood Omar Almutiry Habib Dhahri SEECS National University of Science and TechnologyIslamabadPakistan College of Applied Computer Science King Saud University(Almuzahmiyah Campus)RiyadhSaudi Arabia Department of Software Engineering Foundation University IslamabadPakistan

The COVID-19 outbreak and its medical distancing phenomenon have effectively turned the global healthcare challenge into an opportunity for Telecare Medical Information *** systems employ the latest mobile and digital technologies and provide several advantages like minimal physical contact between patient and healthcare provider,easy mobility,easy access,consistent patient engagement,and *** leakage or unauthorized access to users’medical data can have serious consequences for any medical information *** majority of such systems thus rely on biometrics for authenticated access but biometric systems are also prone to a variety of attacks like spoong,replay,Masquerade,and stealing of stored *** this article,we propose a new cancelable biometric approach which has tentatively been named as“Expression Hash”for Telecare Medical Information *** idea is to hash the expression templates with a set of pseudo-random keys which would provide a unique code(expression hash).This code can then be serving as a template for *** expressions would result in different sets of expression hash codes,which could be used in different applications and for different roles of each *** templates are stored on the server-side and the processing is also performed on the *** proposed technique is a multi-factor authentication system and provides advantages like enhanced privacy and security without the need for multiple biometric *** the case of compromise,the existing code can be revoked and can be directly replaced by a new set of expression hash *** well-known JAFFE(The Japanese Female Facial Expression)dataset has been for empirical testing and the results advocate for the efcacy of the proposed approach.

关键词： Biometrics TMIS biohashing multifactor authentication medical information system

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Automatic Detection of COVID-19 Using a Stacked Denoising Convolutional Autoencoder

引用

Computers, Materials & Continua 2021年第12期69卷 3259-3274页

作者： Habib Dhahri Besma Rabhi Slaheddine Chelbi Omar Almutiry awais mahmood Adel M.Alimi College of Applied Computer Sciences(CACS) King Saud UniversityRiyadh11543Saudi Arabia Faculty of Sciences and Technology of Sidi Bouzid University of KairouanKairouanTunisia National School of Engineers(ENIS) University of SfaxTunisia Department of Computer Sciences College of Sciences and Arts in UnaizahQassim UniversityAl-QassimKingdom of Saudi Arabia

The exponential increase in new coronavirus disease 2019(COVID-19)cases and deaths has made COVID-19 the leading cause of death in many ***,in this study,we propose an efficient technique for the automatic detection of COVID-19 and pneumonia based on X-ray images.A stacked denoising convolutional autoencoder(SDCA)model was proposed to classify X-ray images into three classes:normal,pneumonia,and *** SDCA model was used to obtain a good representation of the input data and extract the relevant features from noisy *** proposed model’s architecture mainly composed of eight autoencoders,which were fed to two dense layers and SoftMax *** proposed model was evaluated with 6356 images from the datasets from different *** experiments and evaluation of the proposed model were applied to an 80/20 training/validation split and for five cross-validation data splitting,*** metrics used for the SDCA model were the classification accuracy,precision,sensitivity,and specificity for both *** results demonstrated the superiority of the proposed model in classifying X-ray images with high accuracy of 96.8%.Therefore,this model can help physicians accelerate COVID-19 diagnosis.

关键词： Stacked autoencoder augmentation multiclassification COVID-19 convolutional neural network

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Novel Framework for Multi-Classification of Guava Disease

引用

Computers, Materials & Continua 2021年第11期69卷 1915-1926页

作者： Omar Almutiry Muhammad Ayaz Tariq Sadad Ikram Ullah Lali awais mahmood Najam Ul Hassan Habib Dhahri College of Applied Computer Sciences King Saud University(Almuzahmiyah Branch)Riyadh11564KSA Department of Computer Science University of Central PunjabLahore54000Pakistan Department of CS&SE International Islamic UniversityIslamabad44000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Department of Electrical and Computer Engineering Dhofar UniversitySalalahOman

Guava is one of the most important fruits in Pakistan,and is gradually boosting the economy of *** production can be interrupted due to different diseases,such as anthracnose,algal spot,fruit fly,styler end rot and *** diseases are usually detected and identified by visual observation,thus automatic detection is required to assist *** this research,a new technique was created to detect guava plant diseases using image processing techniques and computer *** automated system is developed to support farmers to identify major diseases in *** collected healthy and unhealthy images of different guava diseases from the *** image labeling was done with the help of an expert to differentiate between healthy and unhealthy *** local binary pattern(LBP)was used for the extraction of features,and principal component analysis(PCA)was used for dimensionality *** classification was carried out using multiple classifiers,including cubic support vector machine,Fine K-nearest neighbor(F-KNN),Bagged Tree and RUSBoosted Tree algorithms and achieved 100%accuracy for the diagnosis of fruit flies disease using Bagged ***,the findings indicated that cubic support vector machines(C-SVM)was the best classifier for all guava disease mentioned in the dataset.

关键词： Classification guava disease image processing machine learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Visibility Enhancement of Scene Images Degraded by Foggy Weather Condition: An Application to Video Surveillance

引用

Computers, Materials & Continua 2021年第9期68卷 3465-3481页

作者： Ghulfam Zahra Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry awais mahmood Fayez Eid Alazemi Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science and Information Systems College of Business StudiesPAAET12062Kuwait

:In recent years,video surveillance application played a significant role in our daily *** taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the *** reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery,object detection,target killing,and *** remove fog and enhance visibility,a number of visibility enhancement algorithms and methods have been proposed in the ***,these techniques suffer from several limitations that place strong obstacles to the real world outdoor computer vision *** existing techniques do not perform well when images contain heavy fog,large white region and strong atmospheric *** research work proposed a new framework to defog and dehaze the image in order to enhance the visibility of foggy and haze *** proposed framework is based on a Conditional generative adversarial network(CGAN)with two networks;generator and discriminator,each having distinct *** generator network generates fog-free images from foggy images and discriminator network distinguishes between the restored image and the original fog-free *** are conducted on FRIDA dataset and haze *** assess the performance of the proposed method on fog dataset,we use PSNR and SSIM,and for Haze dataset use e,r−,andσas performance *** results shows that the proposed method achieved higher values of PSNR and SSIM which is 18.23,0.823 and lower values produced by the compared method which are 13.94,0.791 and so *** results demonstrated that the proposed framework Has removed fog and enhanced the visibility of foggy and hazy images.

关键词： Video surveillance degraded images image restoration transmission map visibility enhancement

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Defocus blur detection using novel local directional mean patterns(LDMP)and segmentation via KNN matting

引用

Frontiers of Computer Science 2022年第2期16卷 110-122页

作者： awais KHAN Aun IRTAZA Ali JAVED Tahira NAZIR Hafiz MALIK Khalid mahmood MALIK Muhammad Ammar KHAN Department of Computer Science University of Engineering and TechnologyTaxila 47050Pakistan Department of Electrical and Computer Engineering University of MichiganDearbornMI 48128USA Department of Software Engineering University of Engineering and TechnologyTaxila 47050Pakistan Department of Computer Science and Engineering Oakland UniversityMI 48309USA

Detection and segmentation of defocus blur is a challenging task in digital imaging applications as the blurry images comprise of blur and sharp regions that wrap significant information and require effective methods for information *** defocus blur detection and segmentation methods have several limitations i.e.,discriminating sharp smooth and blurred smooth regions,low recognition rate in noisy images,and high computational cost without having any prior knowledge of images i.e.,blur degree and camera ***,there exists a dire need to develop an effective method for defocus blur detection,and segmentation robust to the above-mentioned *** paper presents a novel features descriptor local directional mean patterns(LDMP)for defocus blur detection and employ KNN matting over the detected LDMP-Trimap for the robust segmentation of sharp and blur *** argue/hypothesize that most of the image fields located in blurry regions have significantly less specific local patterns than those in the sharp regions,therefore,proposed LDMP features descriptor should reliably detect the defocus blurred *** fusion of LDMP features with KNN matting provides superior performance in terms of obtaining high-quality segmented regions in the ***,the proposed LDMP features descriptor is robust to noise and successfully detects defocus blur in high-dense noisy *** results on Shi and Zhao datasets demonstrate the effectiveness of the proposed method in terms of defocus blur *** and comparative analysis signify that our method achieves superior segmentation performance and low computational cost of 15 seconds.

关键词： defocus blur detection local directional mean patterns image matting sharpness metrics blur segmentation

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Quantifying Effects of Photoperiod, Temperature and Humidity on Flowering Initiation in Basmati Rice Lines

引用

American Journal of Plant Sciences 2019年第6期10卷 893-903页

作者： Tahir Latif Zulqarnain Haider Muhammad Ramzan Muhammad Akhter Sadia Gull Abid mahmood awais Riaz Rana Ahsen Raza Khan Rice Research Institute Lahore Pakistan Pakistan Agriculture Research Council Kala Shah Kaku Pakistan Yangzhou University Yangzhou China Ayub Agricultural Research Institute Faisalabad Pakistan

The results suggested that all the pure Basmati lines or genotypes initiate flowering within a specific range of day length duration and temperature. Delaying the transplanting date did not significantly affect the flowering time of studied Basmati lines. Maximum threshold of daily minimum temperature (MT) was 24°C during both the years. Likewise, maximum threshold of daily day-length (DL) durations was 12 hours and 18 minutes during both the study years. Results showed that the flowering was maximum when the MT and DL values were optimum as depicted by peak of the trend lines, where maximum lines flowered. Maximum flowering initiations took place when DL was about 11 hours and 15 minutes indicating Basmati as short day plant which flowers maximum when day lengths are shorter and dark or night duration is longer. During 2013, 1st date trial showed strong relationship between flowering initiation with dates of flowering during the flowering period as depicted by higher regression (R2 = 0.837) values. In 2nd date trial during the same year, the value is lower (R2 = 0.513) depicting less relationship of flowering initiation with the dates of flowering. The same trend was observed in 2014 trial. In 1st date trial, strong relationship between flowering initiation with dates of flowering during the flowering period as depicted by higher regression (R2 = 0.864) values, was observed. In 2nd date trial during the same year, the value is lower (R2 = 0.1789) depicting very poor relationship of flowering initiation with the dates of flowering, and the same trend (R2 = 0.0544) in 3rd date of trial.

关键词： Basmati Rice Flowering Photoperiod Temperature Humidity

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：