24,167 datasets found

Using-machine-learning-to-detect-malicious-urls

Phishstorm phishing/legitimate url dataset

Malicious urls dataset

Sms phishing dataset for machine learning and pattern recognition

Smishing and URL Phishing detection datasets

The RenderDiffusion dataset is a dataset used in the paper LN3Diff: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation

The AUTOMI CT dataset, consisting of full-body CT scans from the Humanitas Research Hospital in Milan.

The dataset used in this work, consisting of CT scans of the abdominal region from the CHAOS challenge, and MRI scans of the same region from the CHAOS challenge.

The TikTok dataset is used for human pose estimation task. It contains videos of humans performing different actions.

Video virtual try-on aims to generate realistic sequences that maintain garment identity and adapt to a person's pose and body shape in source videos.

Four different corpora are used for our experiments, which are TIMIT, Aurora-4, AMI, and LibriSpeech. TIMIT contains broadband 16kHz recordings of phonetically-balanced read...

CITY-OSM dataset includes Berlin and Potsdam in Germany, Chicago in the United States, Paris in France, Zurich in Switzerland and Tokyo in Japan, with a total of 1641 aerial...

A private dataset of UAV-borne remote sensing images with a resolution between 10000×10000 and 20000×20000 is constructed. Each remote sensing image which corresponds to the red...

The dataset from the California Transportation Agency contains average traffic speed.

The dataset is used for traffic flow prediction and contains aggregated traffic flow values, vehicle volume, and speed data.

The Tunnel Try-on dataset is a collection of videos with product garment images.

The VVT dataset is a collection of product garment images and corresponding videos.

The VITON-DiT dataset is a collection of unpaired human dance videos that encompasses a wide variety of clothing, backgrounds, and body motions.

Recent years have witnessed the dramatic growth of Internet video traffic, where the video bitstreams are often compressed and delivered in low quality to fit the streamer’s...

Scene segmentation in images is a fundamental yet challenging problem in visual content understanding, which is to learn a model to assign every image pixel to a categorical label.