124 datasets found

Facial expression recognition has been an active area in computer vision with application areas including animation, social robots, personalized banking, etc. In this study,...

ILSVRC-2012-LOC dataset

The dataset used for the experiments on CIFAR-10, CIFAR-100, CINIC-10, SVHN, and ImageNet.

EEG dataset for model test (across-modality & across-subject): To further confirm that our ReAlnet-fMRIs learn more general human brain representations instead of just human...

fMRI dataset for model test (within-modality & across-subject): Although our ReAlnet-fMRIs were trained on individual fMRI signals, we also would like to whether these...

fMRI dataset for model test (within-modality & within-subject): To evaluate whether ReAlnet-fMRIs shows higher similarity to human fMRI representations, we applied the test...

The dataset used in the paper is ImageNet, CSAIL Places, and COWC.

The dataset used in this study for image and text classification tasks.

The ImageNet ILSVRC 2012 validation dataset is used to evaluate the proposed approach.

Deluge Networks are deep neural networks which efficiently facilitate massive cross-layer information inflows from preceding layers to succeeding layers.

The dataset used in this paper is MNIST, CIFAR10, and ImageNet.

The dataset used in the paper is CIFAR-10 and CIFAR-100, ImageNet, and their out-of-distribution variants.

Deep neural networks (DNNs) have achieved remarkable performance across a wide range of applications, while they are vulnerable to adversarial examples, which motivates the...

ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA

Lifelong-CIFAR10 and Lifelong-ImageNet are ever-expanding pools of test samples designed to enhance the robustness of current benchmarks by mitigating the issue of overfitting...

fMRI dataset for model training: The fMRI data originates from Shen et al. (2019). This Shen fMRI dataset recorded human brain fMRI signals from three subjects while they...

The dataset used in the paper is NAS-Bench-301 and AlphaNet. NAS-Bench-301 is a surrogate NAS benchmark built via deep ensembles and modeling uncertainty, which provides...

The MNIST dataset is a large dataset of handwritten digits, and the ImageNet dataset is a large dataset of images.

The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used datasets such as ImageNet and YouTube-8M.

The dataset used in the WaveAttack paper, which consists of four classical benchmark datasets: CIFAR-10, CIFAR-100, GTSRB, and a subset of ImageNet.