Convolutional Neural Networks - Groups

MobileNetV2

The dataset used in this paper is a MobileNetV2 model, which is a type of deep neural network. The dataset is used to evaluate the performance of the proposed heterogeneous system.

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VoxNet

The VoxNet dataset is a benchmark for 3D object recognition.

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Urban100

The dataset used in the paper is a synthetic dataset for blind super-resolution, consisting of low-resolution images and their corresponding blur kernels.

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B100

The dataset used for training and testing the proposed Incremental Residual Learning (IRL) framework.

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Set14

Implicit neural representation, which expresses an image as a continuous function rather than a discrete grid form, is widely used for image processing. The dataset used in this...

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Set5

The dataset used in the paper is a synthetic dataset for blind super-resolution, consisting of low-resolution images and their corresponding blur kernels.

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DIV2K

Single Image Super-Resolution (SR) aims to generate a High Resolution (HR) image I SR from a low resolution (LR) im-age I LR such that it is similar to original HR image I HR....

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U-net: Con-volutional networks for biomedical image segmentation

U-net: Con-volutional networks for biomedical image segmentation.

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Thermal and IR drop analysis using convolutional encoder-decoder networks

Thermal and IR drop analysis using convolutional encoder-decoder networks.

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Learning Multiple Layers of Features from Tiny Images

The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.

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50 datasets found