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https://dspace.univ-ouargla.dz/jspui/handle/123456789/35014| Title: | Soil recognition and features measurement using AI |
| Authors: | Amran, Laila Ferhi, Aya |
| Keywords: | Artificial Intelligence Deep Learning ,CNN Proposed CNN VGG16 ResNet Mobile Net |
| Issue Date: | 2023 |
| Publisher: | UNIVERSITY OF KASDI MERBAH OUARGLA |
| 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. |
| URI: | https://dspace.univ-ouargla.dz/jspui/handle/123456789/35014 |
| Appears in Collections: | Département d'informatique et technologie de l'information - Master |
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