Dataset Search

HazeRD is an outdoor scene dataset for benchmarking dehazing algorithms. HazeRD contains 10 different scenes based on the architectural biometrics project. For each scene, the ground RGB images, depth maps, and synthesized hazy images following the atmospheric optics are provided; the hazy images come with five different haze level using real life physical parameters. The main features of HazeRD to other dehazing datasets are: HazeRD focuses on outdoor scenes whereas other datasets provide indoor scenes; and, the synthesis is based on real life parameters. 

A new methodology to measure coded image/video quality using the just-noticeable-difference (JND) idea was proposed in [1].  Several small JND-based image/video quality datasets were released by the Media Communications Lab at the University of Southern California in [2, 3]. In this work, we present an effort to build a large-scale JND-based coded video quality dataset. The dataset consists of 220 5-second sequences in four resolutions (i.e., 1920x1080, 1280x720, 960x540, and 640x 360).

The files found here are regularly-updated, complete copies of the OpenStreetMap.org database, and those published before the 12 September 2012 are distributed under a Creative Commons Attribution-ShareAlike 2.0 license, those published after are Open Data Commons Open Database License 1.0 licensed.

Test synthetic population produced with WEKA 3.8.

This dataset is a result of my research production into machine learning in android security. The data was obtained by a process that consisted to map a binary vector of permissions used for each application analyzed {1=used, 0=no used}. Moreover, the samples of malware/benign were devided by "Type"; 1 malware and 0 non-malware.

When I did my research, the datasets of malware and benign Android applications were not available, then I give to the community a part of my research results for the future works.

The dataset contains depth frames collected using Microsoft Kinect v1 during the execution of food and drink intake movements.

The dataset contains depth frames collected using Microsoft Kinect v1 during the execution of food and drink intake movements.

The dataset contains depth frames and skeleton joints collected using Microsoft Kinect v2 and acceleration samples provided by an IMU during the execution of the timed up and go test.

The dataset contains depth frames and skeleton joints collected using Microsoft Kinect v2 and acceleration samples provided by an IMU during the simulation of ADLs and falls.

The dataset contains depth frames collected using Microsoft Kinect v1 in top-view configuration and can be used for fall detection.

As part of the Obama Administration’s efforts to make our healthcare system more transparent, affordable, and accountable, the Centers for Medicare & Medicaid Services (CMS) has prepared a public data set, the Medicare Provider Utilization and Payment Data: Physician and Other Supplier Public Use File (Physician and Other Supplier PUF), with information on services and procedures provided to Medicare beneficiaries by physicians and other healthcare professionals.  The Physician and Other Supplier PUF contains information on utilization, payment (allowed amount and Medicare payment)

Demo 2 Zika Virus Data 092216 Abstract

At the intersection of signal processing and information forensics, the Signal Processing Cup 2016 global competition has explored a time-varying location-dependent signature of power grids that can be intrinsically captured in media recordings. This signature is called the Electric Network Frequency (ENF) signals. Throughout the SP Cup 2016 competition, participants were provided with multiple training, practice, and testing datasets that consisted of recordings made in different grids and containing ENF traces.

Zika Demo Abstract

Several established parameters and metrics have been used to characterize the acoustics of a room. The most important are the Direct-To-Reverberant Ratio (DRR), the Reverberation Time (T60) and the reflection coefficient. The acoustic characteristics of a room based on such parameters can be used to predict the quality and intelligibility of speech signals in that room.

This data comes from the Climatological Database for the World's Oceans 1750-1850.  The data includes observational records of ship location, weather data, and other associated data. 

• To encourage research on algorithms that scale to commercial sizes
• To provide a reference dataset for evaluating research
• As a shortcut alternative to creating a large dataset with APIs (e.g. The Echo Nest's)
• To help new researchers get started in the MIR field