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+with+various+pre-trained+Convolutional+Neural+Network+(CNN)+models+for+remote+sensing+(RS)+scene+classification+tasks+using+the+EuroSAT+dataset.+Our+novel+methodology%252C+named+KCN%252C+aims+to+replace+traditional+Multi-Layer+Perceptrons+(MLPs)+with+KAN+to+enhance+classification+performance.+We+employed+multiple+CNN-based+models%252C+including+VGG16%252C+MobileNetV2%252C+EfficientNet%252C+ConvNeXt%252C+ResNet101%252C+and+Vision+Transformer+(ViT)%252C+and+evaluated+their+performance+when+paired+with+KAN.+Our+experiments+demonstrated+that+KAN+achieved+high+accuracy+with+fewer+training+epochs+and+parameters.+Specifically%252C+ConvNeXt+paired+with+KAN+showed+the+best+performance%252C+achieving+94%2525+accuracy+in+the+first+epoch%252C+which+increased+to+96%2525+and+remained+consistent+across+subsequent+epochs.+The+results+indicated+that+KAN+and+MLP+both+achieved+similar+accuracy%252C+with+KAN+performing+slightly+better+in+later+epochs.+By+utilizing+the+EuroSAT+dataset%252C+we+provided+a+robust+testbed+to+investigate+whether+KAN+is+suitable+for+remote+sensing+classification+tasks.+Given+that+KAN+is+a+novel+algorithm%252C+there+is+substantial+capacity+for+further+development+and+optimization%252C+suggesting+that+KCN+offers+a+promising+alternative+for+efficient+image+analysis+in+the+RS+field.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.8e6d514f5cb104da424697f9abc6774d%3frik%3dBhUibRmJ4uKpjA%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Kolmogorov+Arnold+Network+Expression+Example+Python&FORM=IRPRST&ck=9D5B35AAA48CC465C0A4D4EF9FAC26F8&selectedIndex=10&itb=0)
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