Created Datasets for Different Deep Learning Models

All files were derived from the raw dataset for the deep learning algorithms.

Raw dataset (RGB and JPEG)

InceptionV3 RGB

EfficientNet RGB

ResNet18 RGB

ResNet50 RGB

Resnet101 RGB

Darknet19 RGB

Darknet53 RGB

MobileNetV2 RGB

ShuffleNet RGB

600x600 RGB for general-purpose

InceptionV3 Gray Scale

EfficientNet Gray Scale

ResNet18 Gray Scale

ResNet50 Gray Scale

Resnet101 Gray Scale

Darknet19 Gray Scale

Darknet53 Gray Scale

MobileNetV2 Gray Scale

ShuffleNet Gray Scale

600x600 Gray Scale for general-purpose

The dataset with anchor boxes for the hidden circuits)

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For Dr. K. Venkatachalam

Extracted Features from the Images using Deep Learning Models

Extracted Features using EfficientNet RGB

Extracted Features using ResNet18 RGB

Extracted Features using ResNet50 RGB

Extracted Features using Resnet101 RGB

Extracted Features using Darknet19 RGB

Extracted Features using Darknet53 RGB

Extracted Features using MobileNetV2 RGB

Extracted Features using ShuffleNet RGB

Extracted Features using InceptionV3 RGB

Extracted Features using DenseNet201

Extracted Features using Xception

Published Paper

The trained deep learning models can be used for extracting the features from the images.

Trained Deep Learning Models

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