487 datasets found

A novel road rutting dataset containing 949 images from heterogeneous sources.

The DEFAKE dataset is a large-scale dataset for real-world face forgery detection, containing 6,000 images generated by Stable Diffusion.

The dataset used in the Efficient Reward Poisoning Attacks on Online Deep Reinforcement Learning paper.

Thermal images of Laser Powder Bed Fusion fabricated samples utilizing in-situ thermal image monitoring data.

A Deep Reinforcement Learning framework for task arrangement in crowdsourcing platforms.

The dataset is used for deep hashing network for unsupervised domain adaptation.

Feature tracking Cardiac Magnetic Resonance via Deep Learning and Spline Optimization

Large scale deep Convolution Neural Networks (CNNs) increasingly demands the computing power.

The first open-source dental fluorosis image dataset (DFID) is constructed to lay the foundation for deep learning research in dental fluorosis diagnosis.

Aerial robots such as drones have been leveraged to perform bridge inspections. Inspection images with both recognizable structural elements and apparent surface defects can be...

Data augmentation methods have played an important role in the recent advance of deep learning models, and have become an indispensable component of state-of-the-art models in...

The dataset used in the paper is a large-scale graph dataset, consisting of users and shows with multi-attribute edges. The graph is constructed by selecting user IDs and side...

The dataset used in this paper is a collection of convolutional neural network (CNN) weights, which are compressed using transform quantization.

The dataset used in this paper is the SqueezeNet v1.1 and ZynqNet CNNs, which are characterized by small model size and limited computational requirements.

Supervised-contrastive loss (SCL) is an alternative to cross-entropy (CE) for classification tasks that makes use of similarities in the embedding space to allow for richer...

A successive subspace learning model, termed VoxelHop, for accurate classification of Amyotrophic Lateral Sclerosis (ALS) using T2-weighted structural MRI data.

A dataset for road damage detection and classification using deep neural networks with smartphone images.

The dataset used in the paper is a collection of experiences sampled from a replay buffer, used to train and evaluate the proposed Multi-step DDPG (MDDPG) and Mixed Multi-step...

The fastMRI AXT1 multi-coil brain dataset is consisted of 248 training volumes (3844 slices) and 82 validation (1424 slices) validation volumes.

Building Data Genome 2.0 (BDG2.0) dataset comprises hourly time-series data from electrical meters, sourced from the BDG2 project, for modeling purposes.