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https://dspace.univ-ouargla.dz/jspui/handle/123456789/35014
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DC Field | Value | Language |
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dc.contributor.author | Amran, Laila | - |
dc.contributor.author | Ferhi, Aya | - |
dc.date.accessioned | 2023-11-14T10:33:44Z | - |
dc.date.available | 2023-11-14T10:33:44Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://dspace.univ-ouargla.dz/jspui/handle/123456789/35014 | - |
dc.description.abstract | Soilplaysanimportantroleinthequalityofagriculturalcrops,especiallysinceweareinanera inwhichtheagriculturalsectoroccupiesagreatimportancenotonlyfromthesideoftheeconomy,butalsofromthesideofachievingfoodsufficiency,soifthetypeofthesoilisnotappropriate,thentheproductwillnotbeoftherequiredquality. Inourresearch,wewantedtohelpevery farmerandpeasantandeveryoneinterestedinthisfieldbydevelopingawebsitethatallowssoil classification(initiallyfivetypes)byincludingapictureofthesoiltoknowitstype. TheclassificationprocesswascarriedoutusingdeeplearningexactlyProposedCNNmodel,whichhadthe highestaccuracy(86%)aftercomparingitwith3othermodels,VGG(80%),ResNet(79%),and MobileNet(76%). Intheend,aftertheclassificationisdone,themostimportantcharacteristics (sixcharacteristics)ofthatsoilarepresented,whitchistemperature,Ph,Porosity,texture,color ,density. | en_US |
dc.language.iso | en | en_US |
dc.publisher | UNIVERSITY OF KASDI MERBAH OUARGLA | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | ,CNN | en_US |
dc.subject | Proposed CNN | en_US |
dc.subject | VGG16 | en_US |
dc.subject | ResNet | en_US |
dc.subject | Mobile Net | en_US |
dc.title | Soil recognition and features measurement using AI | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Département d'informatique et technologie de l'information - Master |
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