Changes

<gallery mode!--Start of table definition-->{|style="background:transparent; color:black" border="0" height="packed550" heightsalign="350center">valign="bottom" cellpadding=10px cellspacing=0px|-align="center"||[[File:Resnet50 train and validation accuracy.png|border|500x500px|none]]||[[File:Resnet50 train and validation loss.png|border|500x500px|none]]||-align="center" valign="top"|width="25"||width="100"|Train and validation accuracy trend over 1000 training epochs for ResNet50 modelFile:Resnet50 train and validation loss.png|width="25"||width="100"|Train and validation loss trend over 1000 training epochs for ResNet50 model</gallery>|width="25"||}

<gallery mode!--Start of table definition-->{|style="background:transparent; color:black" border="0" height="packed550" heightsalign="350center">valign="bottom" cellpadding=10px cellspacing=0px|-align="center"||[[File:Resnet101 train and validation accuracy.png|border|500x500px|none]]||[[File:Resnet101 train and validation loss.png|border|500x500px|none]]||-align="center" valign="top"|width="25"||width="100"|Train and validation accuracy trend over 1000 training epochs for ResNet101 modelFile:Resnet101 train and validation loss.png|width="25"||width="100"|Train and validation loss trend over 1000 training epochs for ResNet101 model</gallery>|width="25"||}

<gallery mode!--Start of table definition-->{|style="background:transparent; color:black" border="0" height="packed550" heightsalign="350center">valign="bottom" cellpadding=10px cellspacing=0px|-align="center"||[[File:Resnet152 train and validation accuracy.png|border|500x500px|none]]||[[File:Resnet152 train and validation loss.png|border|500x500px|none]]||-align="center" valign="top"|width="25"||width="100"|Train and validation accuracy trend over 1000 training epochs for ResNet152 modelFile:Resnet152 train and validation loss.png|width="25"||width="100"|Train and validation loss trend over 1000 training epochs for ResNet152 model</gallery>|width="25"||}

<gallery mode!--Start of table definition-->{|style="background:transparent; color:black" border="0" height="packed550" heightsalign="350center">valign="bottom" cellpadding=10px cellspacing=0px|-align="center"||[[File:InceptionV4 train and validation accuracy.png|border|500x500px|none]]||[[File:InceptionV4 train and validation loss.png|border|500x500px|none]]||-align="center" valign="top"|width="25"||width="100"|Train and validation accuracy trend over 1000 training epochs for InceptionV4 modelFile:InceptionV4 train and validation loss.png|width="25"||width="100"|Train and validation loss trend over 1000 training epochs for InceptionV4 model</gallery>|width="25"||}

<gallery mode!--Start of table definition-->{|style="background:transparent; color:black" border="0" height="550" align="center" valign="packedbottom" heightscellpadding=10px cellspacing=0px|-align="350center">||[[File:Inception ResNet V1 train and validation accuracy.png|border|500x500px|none]]||[[File:Inception ResNet V1 train and validation loss.png|border|500x500px|none]]||-align="center" valign="top"|width="25"||width="100"|Train and validation accuracy trend over 1000 training epochs for Inception ResNet V1 modelFile:Inception ResNet V1 train and validation loss.png|width="25"||width="100"|Train and validation loss trend over 1000 training epochs for Inception ResNet V1 model</gallery>|width="25"||}

<gallery mode!--Start of table definition-->{|style="packedbackground:transparent; color:black" heightsborder="3500">height="550" align="center" valign="bottom" cellpadding=10px cellspacing=0px|-align="center"||[[File:Inception ResNet V2 train and validation accuracy.png|border|500x500px|none]]||[[File:Inception ResNet V2 train and validation loss.png|border|500x500px|none]]||-align="center" valign="top"|width="25"||width="100"|Train and validation accuracy trend over 1000 training epochs for Inception ResNet V2 modelFile:Inception ResNet V2 train and validation loss.png|width="25"||width="100"|Train and validation loss trend over 1000 training epochs for Inception ResNet V2 model</gallery>|width="25"||}