检索结果-南通市图书馆

Optimal Artificial Intelligence Based Automated Skin Lesion Detection and Classification Model

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

Computer Systems Science & Engineering 2023年第1期44卷 693-707页

作者： Kingsley A.Ogudo R.Surendran Osamah Ibrahim khalaf Faculty of Engineering and the Built Environment Department of Electrical and Electronics Engineering TechnologyUniversity of JohannesburgJohannesburg2006South Africa Center for Artificial Intelligence and Research(CaiR) Chennai Institute of TechnologyChennai600069India Al-Nahrain Nanorenewable Energy Research Center Al-Nahrain UniversityBaghdad64074Iraq

Skin lesions have become a critical illness worldwide,and the earlier identification of skin lesions using dermoscopic images can raise the survival *** of the skin lesion from those dermoscopic images will be a tedious *** accuracy of the classification of skin lesions is improved by the use of deep learning ***,convolutional neural networks(CNN)have been established in this domain,and their techniques are extremely established for feature extraction,leading to enhanced *** this motivation,this study focuses on the design of artificial intelligence(ai)based solutions,particularly deep learning(DL)algorithms,to distinguish malignant skin lesions from benign lesions in dermoscopic *** study presents an automated skin lesion detection and classification technique utilizing optimized stacked sparse autoen-coder(OSSAE)based feature extractor with backpropagation neural network(BPNN),named the OSSAE-BPNN *** proposed technique contains a multi-level thresholding based segmentation technique for detecting the affected lesion *** addition,the OSSAE based feature extractor and BPNN based classifier are employed for skin lesion ***,the parameter tuning of the SSAE model is carried out by the use of sea gull optimization(SGO)*** showcase the enhanced outcomes of the OSSAE-BPNN model,a comprehensive experimental analysis is performed on the benchmark *** experimentalfindings demonstrated that the OSSAE-BPNN approach outper-formed other current strategies in terms of several assessment metrics.

关键词： Deep learning dermoscopic images intelligent models machine learning skin lesion

Human Emotions Classification Using EEG via Audiovisual Stimuli and ai

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第12期73卷 5075-5089页

作者： abdullah A Asiri Akhtar Badshah Fazal Muhammad Hassan A Alshamrani Khalil Ullah khalaf A Alshamrani Samar Alqhtani Muhammad Irfan Hanan Talal Halawani Khlood M Mehdar Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Software Engineering University of MalakandDir LowerPakistan Department of Computer Science and Information Systems College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia

Electroencephalogram(EEG)is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain,measured and recorded chronologically the surface of the scalp from the *** recorded signals from the brain are rich with useful *** inference of this useful information is a challenging *** paper aims to process the EEG signals for the recognition of human emotions specifically happiness,anger,fear,sadness,and surprise in response to audiovisual *** EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp,in response to audiovisual stimuli for the mentioned *** a bandpass filter with a bandwidth of 1-100 Hz,recorded raw EEG signals are *** preprocessed signals then further analyzed and twelve selected features in different domains are *** Random forest(RF)and multilayer perceptron(MLP)algorithms are then used for the classification of the emotions through extracted *** proposed audiovisual stimuli based EEG emotion classification system shows an average classification accuracy of 80%and 88%usingMLP and RF classifiers respectively on hybrid features for experimental signals of different *** proposed model outperforms in terms of cost and accuracy.

关键词： Electroencephalography emotion classification signal processing multilayer perceptron random forest

Flow over Broad Crested Weirs： Comparison of 2D and 3D Models

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Civil Engineering and Architecture 2017年第8期11卷 769-779页

作者： Shaymaa A. M. Al-Hashimi Huda M. Madhloom Rasul M. khalaf Thameen N. Nahi Nadhir A. ai-Ansari Department of Civil Engineering Al-Mustansiriayah University Baghdad 1001Iraq Department of Civil Environmental and Natural Resources Engineering Lulea University of Technology 97187 Lulea Sweden

Activity of Insect Fauna during the Night in the Pa Orchards of Central Iraq

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Food Science and Engineering 2012年第5期2卷 277-282页

作者： Mohammed Zaidan khalaf Ali Khaywon ShbarI Falah Hansh Naher Noel Franso Jabo Bushra HasanAbdulalhamza Rajaa Aboud Sami IPM Center Ministry of Science ＆ Technology Baghdad Iraq

An International Journalism Model of Professionalism in News Production： The Concepts and the Measurements

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journalism and Mass Communication 2016年第4期6卷 169-186页

作者： khalaf Tahat Yarmouk University Irbid Jordan

Definition and Development of a Control Concept Applied in Elements Distributed for Manage Them Using IoT

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal on Internet of Things 2021年第3期3卷 87-97页

作者： Jesus Hamilton Ortiz Osamah Ibrahim khalaf Fernando Velez Varela Nicolas Minotta Rodriguez Christian Andres Mosquera Gil Closemobile R&D Madrid28031Spain ai-Nahrain University Baghdad10072Iraq Universidad Libre Seccional Cali Cali760033Colombia

In recent years,the Internet has gradually developed into a mature tool,which can integrate technologies involved in different application *** Internet allows the integration of solutions to different problems,which benefits both users and *** Internet of Things is a further development of the Internet,which can further realize the interconnection of people,machines,and *** work of this paper mainly focuses on the use of Internet of Things technology to achieve efficient management.A wireless device is designed in the paper,which can be integrated in a *** helmet can be used in some specific *** can use the Internet of Things technology to call the data generated by the hearing equipment and lighting equipment in the helmet to identify *** helmets can be managed through a network *** the network platform,in addition to the helmet,some other components can be allowed to access,making the platform more universal and *** paper elaborates on the design and development of the project and shows how to use it for effective time management in the skating rink.

关键词： Helmet skating rink telemetry users management web application