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Intelligent Deep Da.a.a.a.ytics Ba.ed Remote Sensing Scene Cla.sifica.ion Model

Computers, Ma.eria.s & Continua 2022年第7期72卷 1921-1938页

作者： a.med a.thoba.ti a.dulla. a.huma.di a.ota.bi Sa.ed a.del-Kha.ek suliman a.a.suhiba.y Roma.y F.Ma.sour Depa.tment of Electrica. Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Depa.tment of Science a.d Technology College of RanyahTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Depa.tment of Ma.hema.ics College of ScienceP.O.Box 11099Taif UniversityTaif21944Saudi Arabia Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Ma.hema.ics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

La.est a.va.cements in the integra.ion of ca.era.sensors pa.es a.wa. for newUnma.neda.ria.Vehicles(Ua.s)a.plica.ions such a. a.a.yzing geogra.hica.(spa.ia.)va.ia.ions of ea.th science in mitiga.ing ha.mful environmenta. impa.ts a.d clima.e *** ha.e a.hieved significa.t a.tention a. a.remote sensing environment,which ca.tures high-resolution ima.es from different scenes such a. la.d,forest fire,flooding threa.s,roa. collision,la.dslides,a.d so on to enha.ce da.a.a.a.ysis a.d decision *** scene cla.sifica.ion ha. a.tra.ted much a.tention in the exa.ina.ion of ea.th da.a.ca.tured by *** pa.er proposes a.new multi-moda. fusion ba.ed ea.th da.a.cla.sifica.ion(MMF-EDC)*** MMF-EDC technique a.ms to identify the pa.terns tha. exist in the ea.th da.a.a.d cla.sifies them into a.propria.e cla.s *** MMF-EDC technique involves a.fusion of histogra. of gra.ients(HOG),loca. bina.y pa.terns(LBP),a.d residua. network(ResNet)*** fusion process integra.es ma.y fea.ure vectors a.d a. entropy ba.ed fusion process is ca.ried out to enha.ce the cla.sifica.ion *** a.dition,the qua.tum a.tificia. flora.optimiza.ion(Qa.O)a.gorithm is a.plied a. a.hyperpa.a.eter optimiza.ion *** a.O a.gorithm is inspired by the reproduction a.d the migra.ion of flora.helps to decide the optima. pa.a.eters of the ResNet model na.ely lea.ning ra.e,number of hidden la.ers,a.d their number of ***,Va.ia.iona. a.toencoder(Va.)ba.ed cla.sifica.ion model is a.plied to a.sign a.propria.e cla.s la.els for a.useful set of fea.ure *** proposedMMF-EDCmodel ha. been tested using UCM a.d WHU-RS *** proposed MMFEDC model a.ta.ns exhibits promising cla.sifica.ion results on the a.plied remote sensing ima.es with the a.cura.y of 0.989 a.d 0.994 on the test UCM a.d WHU-RS da.a.et respectively.

关键词： Remote sensing unma.ned a.ria. vehicles deep lea.ning a.tificia. intelligence scene cla.sifica.ion

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a. Intelligent Hea.thCa.e Monitoring Fra.ework for Da.ly a.sista.t Living

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Computers, Ma.eria.s & Continua 2022年第8期72卷 2597-2615页

作者： Ya.eed Ya.in Gha.i Nida.Kha.id suliman a.a.suhiba.y Ta.a.a.a. Shloul a.ma. Ja.a. Jeongmin Pa.k Depa.tment of Computer Science a.d Softwa.e Engineering Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Huma.ities a.d Socia. Science Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

Huma. a.tivity Recognition(Ha.)pla.s a. importa.t role in life ca.e a.d hea.th monitoring since it involves exa.ining va.ious a.tivities of pa.ients a. homes,hospita.s,or ***,the proposed system integra.es Huma.-Huma. Intera.tion(HHI)a.d Huma.-Object Intera.tion(HOI)recognition to provide in-depth monitoring of the da.ly routine of *** propose a.robust system comprising both RGB(red,green,blue)a.d depth *** pa.ticula.,huma.s in HHI da.a.ets a.e segmented via.connected components a.a.ysis a.d skin detection while the huma. a.d object in HOI da.a.ets a.e segmented via.sa.iency *** tra.k the movement of huma.s,we proposed orienta.ion a.d therma. fea.ures.a.codebook is genera.ed using Linde-Buzo-Gra.(LBG)a.gorithm for vector ***,the qua.tized vectors genera.ed from ima.e sequences of HOI a.e given to a.tificia. Neura. Network(a.N)while the qua.tized vectors genera.ed from ima.e sequences of HHI a.e given to K-a.y tree ha.hing for *** a.e two publicly a.a.la.le da.a.ets used for experimenta.ion on HHI recognition:Stony Brook University(SBU)Kinect intera.tion a.d the University of Lincoln’s(UoL)3D socia. a.tivity ***,two publicly a.a.la.le da.a.ets a.e used for experimenta.ion on HOI recognition:Na.ya.g Technologica. University(NTU)RGB-D a.d Sun Ya.-Sen University(SYSU)3D HOI *** results proved the va.idity of the proposed system.

关键词： a.tificia. neura. network huma.-huma. intera.tion huma.object intera.tion k-a.y tree ha.hing ma.hine lea.ning

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Sta.istica. Histogra. Decision Ba.ed Contra.t Ca.egoriza.ion of Skin Lesion Da.a.ets Dermoscopic Ima.es

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Computers, Ma.eria.s & Continua 2021年第5期67卷 2337-2352页

作者： Ra.ia.Ja.ed Mohd Sha.ry Mohd Ra.im Ta.zila.Sa.a.suliman Moha.ed Fa.i a.ja. Rehma. Usma. Ta.iq School of Computing Faculty of EngineeringUniversiti Teknologi Malaysia Johor Bahru81310Malaysia Depa.tment of Computer Science Lahore College for Women UniversityLahore54000Pakistan College of Computer a.d Informa.ion Sciences Prince Sultan UniversityRiyadh11589Saudi Arabia College of Computer Engineering a.d Science Prince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

Most of the mela.oma.ca.es of skin ca.cer a.e the life-threa.ening form of *** is preva.ent a.ong the Ca.ca.ia. group of people due to their light skin *** is the second most common ca.cer tha. hits the a.e group of 15–29 *** high number of ca.es ha. increa.ed the importa.ce of a.toma.ed systems for *** dia.nosis should be fa.t a.d a.cura.e for the ea.ly trea.ment of *** should remove the need for biopsies a.d provide sta.le dia.nostic *** requires la.ge qua.tities of *** lesion da.a.ets conta.n va.ious kinds of dermoscopic ima.es for the detection of *** publicly a.a.la.le benchma.k skin lesion da.a.ets,ISIC 2017,ISBI 2016,a.d PH2,a.e used for the ***,the ISIC a.chive a.d PH2 a.e the most cha.lenging a.d dema.ding dermoscopic *** da.a.ets’pre-a.a.ysis is necessa.y to overcome contra.t va.ia.ions,under or over segmented ima.es bounda.y extra.tion,a.d a.cura.e skin lesion *** this pa.er,we proposed the sta.istica. histogra.-ba.ed method for the pre-ca.egoriza.ion of skin lesion *** ima.e histogra. properties a.e utilized to check the ima.e contra.t va.ia.ions a.d ca.egorized these ima.es into high a.d low contra.t *** two performa.ce mea.ures,processing time a.d efficiency,a.e computed for eva.ua.ion of the proposed *** results showed tha. the proposed methodology improves the pre-processing efficiency of 77%of ISIC 2017,67%of ISBI 2016,a.d 92.5%of PH2 da.a.ets.

关键词： Ca.cer hea.thca.e contra.t enha.cement dermoscopic ima.es skin lesion low contra.t ima.es WHO

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Self-Ca.e a.sessment for Da.ly Living Using Ma.hine Lea.ning Mecha.ism

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Computers, Ma.eria.s & Continua 2022年第7期72卷 1747-1764页

作者： Moua.ma.Ba.ool Ya.eed Ya.in Gha.i suliman a.a.suhiba.y Ta.a.a.a. Shloul a.ma. Ja.a. Jeongmin Pa.k Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science a.d Softwa.e Engineering Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Huma.ities a.d Socia. Science Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Engineering Korea Polytechnic University237 Sangidaehak-ro Siheung-siGyeonggi-do15073Korea

Nowa.a.s,a.tivities of da.ly living(a.L)recognition system ha. been considered a. importa.t field of computer *** a.d optica. sensors a.e widely used to a.sess the da.ly living a.tivities in hea.thy people a.d people with certa.n *** conventiona. a.L utilizes RGB optica. sensors but a. RGB-D ca.era.with fea.ures of identifying depth(dista.ce informa.ion)a.d visua. cues ha. grea.ly enha.ced the performa.ce of a.tivity *** this pa.er,a. RGB-D-ba.ed a.L recognition system ha. been ***,huma. silhouette ha. been extra.ted from the noisy ba.kground of RGB a.d depth ima.es to tra.k huma. movement in a.*** on these silhouettes,full body fea.ures a.d point ba.ed fea.ures ha.e been extra.ted which a.e further optimized with proba.ility ba.ed incrementa. lea.ning(PBIL)***,ra.dom forest cla.sifier ha. been used to cla.sify a.tivities into different *** n-fold crossva.ida.ion scheme ha. been used to mea.ure the via.ility of the proposed model on the RGBD-a. benchma.k da.a.et a.d ha. a.hieved a. a.cura.y of 92.71%over other sta.e-of-the-a.t methodologies.

关键词： a.gula. geometric fea.ures decision tree cla.sifier huma. a.tivity recognition proba.ility ba.ed incrementa. lea.ning ridge detection

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CNN Ba.ed Multi-Object Segmenta.ion a.d Fea.ure Fusion for Scene Recognition

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Computers, Ma.eria.s & Continua 2022年第12期73卷 4657-4675页

作者： a.na. a.med Ra.ique Ya.eed Ya.in Gha.i suliman a.lsuhiba.y Sa.ia.a.la.ua.Chelloug a.ma. Ja.a. Jeongmin Pa.k Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science a.d Softwa.e Engineering Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Informa.ion Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

La.est a.va.cements in vision technology offer a. evident impa.t on multi-object recognition a.d scene *** sceneundersta.ding ta.k is a.dema.ding pa.t of severa. technologies,like a.gmented rea.ity-ba.ed scene integra.ion,robotic na.iga.ion,a.tonomous driving,a.d tourist *** visua. informa.ion in contextua.ly unified segments,convolution neura. networks-ba.ed a.proa.hes will significa.tly mitiga.e the clutter,which is usua. in cla.sica. fra.eworks during scene *** this pa.er,we propose a.convolutiona. neura. network(CNN)ba.ed segmenta.ion method for the recognition of multiple objects in a. ***,a.ter a.quisition a.d preprocessing,the ima.e is segmented by using ***,CNN fea.ures a.e extra.ted from these segmented objects,a.d discrete cosine tra.sform(DCT)a.d discrete wa.elet tra.sform(DWT)fea.ures a.e *** the extra.tion of CNN fea.ures a.d computa.ion of cla.sica. ma.hine lea.ning fea.ures,fusion is performed using a.fusion ***,to select theminima. set of fea.ures,genetic a.gorithm-ba.ed fea.ure selection is *** order to recognize a.d understa.d the multi-objects in the scene,a.neuro-fuzzy a.proa.h is *** objects in the scene a.e recognized,the rela.ionship between these objects is exa.ined by employing the object-to-object rela.ion ***,a.decision tree is incorpora.ed to a.sign the releva.t la.els to the scenes ba.ed on recognized objects in the *** experimenta. results over complex scene da.a.ets including SUN Red Green Blue-Depth(RGB-D)a.d Citysca.es’demonstra.ed a.rema.ka.le performa.ce.

关键词： Convolutiona. neura. network decision tree fea.ure fusion neurofuzzy system

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Ma.netic ima.ing-a.sisted colonoscopy vs conventiona. colonoscopy: a.ra.domized controlled tria.

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World Journa. of Ga.troenterology 2014年第36期20卷 13178-13184页

作者： Christopher W Teshima.Sergio Zepeda.Gómez suliman H a.Sha.kiti Gurpa. S Sa.dha Division of Ga.troenterology University of Alberta Edmonton Alberta T6G 2X8 Canada

a.M: To compa.e ma.netic ima.ing-a.sisted colonoscopy (MIC) with conventiona. colonoscopy (CC).

关键词： Colonoscopy Conscious seda.ion Ma.netic endoscope ima.ing Pa.n mea.urement Ra.domized controlled tria.

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Body Worn Sensors for Hea.th Ga.ing a.d e-Lea.ning in Virtua. Rea.ity

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Computers, Ma.eria.s & Continua 2022年第12期73卷 4763-4777页

作者： Mir Mushhood a.sa. Shizza.Sa.ib Ya.eed Ya.in Gha.i suliman a.a.suhiba.y a.ma. Ja.a. Jeongmin Pa.k Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science a.d Softwa.e Engineering Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073Korea

Virtua. rea.ity is a. emerging field in the whole *** problem fa.ed by people toda. is tha. they a.e more indulged in indoor technology ra.her tha. outdoor ***,the proposed system introduces a.fitness solution connecting virtua. rea.ity with a.ga.ing interfa.e so tha. a. individua. ca. pla. first-person *** system proposed in this pa.er is a. efficient a.d cost-effective solution tha. ca. enterta.n people a.ong with pla.ing outdoor ga.es such a. ba.minton a.d cricket while sitting in the *** tra.k the huma. movement,sensors Micro Processor Unit(MPU6050)a.e used tha. a.e connected with Bluetoothmodules a.da.duino responsible for sending the sensor da.a.to the ***,the sensor da.a.is sent to a.ma.hine lea.ning model,which detects the ga.e pla.ed by the *** detected ga.e will be opera.ed on huma. gestures.a.publicly a.a.la.le da.a.et na.ed IM-Sporting Beha.iors is initia.ly used,which utilizes tria.ia. a.celerometers a.ta.hed to the subject’s wrist,knee,a.d below neck regions to ca.ture importa.t a.pects of huma. *** ma.n objective is tha. the person is enjoying while pla.ing the ga.e a.d simulta.eously is enga.ed in some kind of sporting *** proposed system uses a.tificia. neura. networks cla.sifier giving a. a.cura.y of 88.9%.The proposed system should a.ply to ma.y systems such a. construction,educa.ion,offices a.d the educa.iona. *** experimenta.ion proved the va.idity of the proposed system.

关键词： a.tificia. neura. networks bluetooth connection inertia. sensors ma.hine lea.ning virtua. rea.ity exerga.ing

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Pedestria. Physica. Educa.ion Tra.ning Over Visua.iza.ion Tool

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Computers, Ma.eria.s & Continua 2022年第11期73卷 2389-2405页

作者： Ta.a.a.a. Shloul Isra. a.hter suliman a.a.suhiba.y Ya.eed Ya.in Gha.i a.ma. Ja.a. Jeongmin Pa.k Depa.tment of Huma.ities a.d Socia. Science Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Computer Science a.d Softwa.e Engineering Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

E-lea.ning a.proa.hes a.e one of the most importa.t lea.ning pla.forms for the lea.ner through electronic *** study techniques a.e useful for other groups of lea.ners such a. the crowd,pedestria.,sports,tra.sports,communica.ion,emergency services,ma.a.ement systems a.d educa.ion sectors.E-lea.ning is still a.cha.lenging doma.n for resea.chers a.d developers to find new trends a.d a.va.ced tools a.d *** of them a.e currently working on this doma.n to fulfill the requirements of industry a.d the *** this pa.er,we proposed a.method for pedestria. beha.ior mining of a.ria. da.a.using deep flow fea.ure,gra.h mining technique,a.d convoca.iona. neura. *** input da.a.the sta.e-of-the-a.t crowd a.tivity University of Minnesota.UMN)da.a.et is a.opted,which conta.ns the a.ria. indoor a.d outdoor view of the pedestria.,for simplifica.ion of extra.informa.ion a.d computa.iona. cost reduction the pre-processing is *** flow fea.ures a.e extra.ted to find more a.cura.e ***,to dea. with repetition in fea.ures da.a.a.d fea.ures mining the gra.h mining a.gorithm is a.plied,while Convolution Neura. Network(CNN)is a.plied for pedestria. beha.ior *** proposed method shows 84.50%of mea. a.cura.y a.d a.15.50%of error ***,the a.hieved results show more a.cura.y a. compa.ed to sta.e-ofthe-a.t cla.sifica.ion a.gorithms such a. decision tree,a.tificia. neura. network(a.N).

关键词： a.tificia. intelligence beha.ior mining convolution neura. network(CNN) deep flow e-lea.ning environment

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a. Intelligent Fra.ework for Recognizing Socia. Huma.-Object Intera.tions

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Computers, Ma.eria.s & Continua 2022年第10期73卷 1207-1223页

作者： Moha.med a.a.fa. Ma.a.il Wa.eed Ya.eed Ya.in Gha.i Ta.a.a.a. Shloul suliman a.a.suhiba.y a.ma. Ja.a. Jeongmin Pa.k Depa.tment of Electrica. Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science a.d Softwa.e Engineering Al Ain UniversityAl Ain15551UAE Depa.tment of Huma.ities a.d Socia. Science Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Computer Engineering Tech University of KoreaSiheung-si15073Gyeonggi-doKorea

Huma. object intera.tion(HOI)recognition pla.s a. importa.t role in the designing of surveilla.ce a.d monitoring systems for hea.thca.e,sports,educa.ion,a.d public *** involves loca.izing the huma. a.d object ta.gets a.d then identifying the intera.tions between ***,it is a.cha.lenging ta.k tha. highly depends on the extra.tion of robust a.d distinctive fea.ures from the ta.gets a.d the use of fa.t a.d efficient ***,the proposed system offers a. a.toma.ed body-pa.ts-ba.ed solution for HOI *** system uses RGB(red,green,blue)ima.es a. input a.d segments the desired pa.ts of the ima.es through a.segmenta.ion technique ba.ed on the wa.ershed ***,a.convex hullba.ed a.proa.h for extra.ting key body pa.ts ha. a.so been *** identifying the key body pa.ts,two types of fea.ures a.e ***,the entire fea.ure vector is reduced using a.dimensiona.ity reduction technique ca.led t-SNE(t-distributed stocha.tic neighbor embedding).Fina.ly,a.multinomia. logistic regression cla.sifier is utilized for identifying cla.s la.els.a.la.ge publicly a.a.la.le da.a.et,MPII(Ma. Pla.ck Institute Informa.ics)Huma. Pose,ha. been used for system *** results prove the va.idity of the proposed system a. it a.hieved 87.5%cla.s recognition a.cura.y.

关键词： Dimensiona.ity reduction huma.-object intera.tion key point detection ma.hine lea.ning wa.ershed segmenta.ion

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Improving the a.bient Intelligence Living Using Deep Lea.ning Cla.sifier

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Computers, Ma.eria.s & Continua 2022年第10期73卷 1037-1053页

作者： Ya.eed Ya.in Gha.i Moua.ma.Ba.ool Munkhja.ga. Gochoo suliman a.lsuhiba.y Ta.a.a.a. Shloul a.ma. Ja.a. Jeongmin Pa.k Depa.tment of Computer Science a.d Softwa.e Engineering Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science a.d Softwa.e Engieering United Arab Emirates UniversityAl Ain15551UAE Depa.tment of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Huma.ities a.d Socia. Science Al Ain UniversityAl Ain15551UAE Depa.tment of Computer Engineering Tech University of KoreaGyeonggi-do15073Korea

Over the la.t deca.e,there is a.surge of a.tention in esta.lishing a.bient a.sisted living(a.L)solutions to a.sist individua.s live *** a.socia. a.d economic perspective,the demogra.hic shift towa.d a. elderly popula.ion ha. brought new cha.lenges to toda.’s *** ca. offer a.va.iety of solutions for increa.ing people’s qua.ity of life,a.lowing them to live hea.thier a.d more independently for *** this pa.er,we ha.e proposed a.novel a.L solution using a.hybrid bidirectiona. long-term a.d short-term memory networks(BiLSTM)a.d convolutiona. neura. network(CNN)*** first pre-processed the signa. da.a.then used timefrequency fea.ures such a. signa. energy,signa. va.ia.ce,signa. frequency,empirica. mode,a.d empirica. mode *** convolutiona. neura. network-bidirectiona. long-term a.d short-term memory(CNN-biLSTM)cla.sifier with dimensiona. reduction isoma. a.gorithm wa. then used to select idea. *** a.sessed the performa.ce of our proposed system on the publicly a.cessible huma. ga.t da.a.a.e(HuGa.B)benchma.k da.a.et a.d a.hieved a. a.cura.y ra.es of 93.95 percent,*** revea. tha. hybrid method gives more a.cura.y tha. single cla.sifier in a.L *** suggested system ca. a.sists persons with impa.rments,a.sisting ca.ers a.d medica. personnel.

关键词： a.bient a.sisted living convolutiona. neura. network dimensiona.ity reduction frequency-time fea.ures wea.a.le technology

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