The Electricity Transformer Temperature (ETT) is a crucial indicator in the electric power long-term deployment. This dataset consists of 2 years data from two separated counties in China. To explore the granularity on the Long sequence time-series forecasting (LSTF) problem, different subsets are created, {ETTh1, ETTh2} for 1-hour-level and ETTm1 for 15-minutes-level. Each data point consists of the target value ”oil temperature” and 6 power load features. The train/val/test is 12/4/4 months.
278 PAPERS • 27 BENCHMARKS
This dataset contains expert-labeled telemetry anomaly data from the Mars Science Laboratory (MSL) rover, Curiosity.
120 PAPERS • 1 BENCHMARK
QM9 provides quantum chemical properties (at DFT level) for a relevant, consistent, and comprehensive chemical space of small organic molecules. This database may serve the benchmarking of existing methods, development of new methods, such as hybrid quantum mechanics/machine learning, and systematic identification of structure-property relationships.
63 PAPERS • 7 BENCHMARKS
Weather is recorded every 10 minutes for the 2020 whole year, which contains 21 meteorological indicators, such as air temperature, humidity, etc. The dataset in CSV format can be downloaded at https://drive.google.com/file/d/1Tc7GeVN7DLEl-RAs-JVwG9yFMf--S8dy/view?usp=share_link.
28 PAPERS • 10 BENCHMARKS
Forecast Sales using ARIMA and SARIMA
3 PAPERS • 1 BENCHMARK
Overview The edeniss2020 dataset is a time series dataset. It consists of equidistant sensor readings stemming from 97 sensors in the EDEN ISS research greenhouse.
2 PAPERS • NO BENCHMARKS YET
Single cortical neurons as deep artificial neural networks This dataset contains training and testing subsets of the input/output relationship of a single cortical layer 5 pyramidal cell (L5PC) neuron at 1ms single spike temporal resolution. The data is obtained via a simulation that contains all of the currently (2021) known and well modeled "messy biological details" that relate to the operation of single neurons in the brain.
2 PAPERS • 1 BENCHMARK
Recorded with a Husky A200 wheeled UGV, BorealTC contains 116 min of Inertial Measurement Unit (IMU), motor current, and wheel odometry data, focusing on typical boreal forest terrains, notably snow, ice, and silty loam. The dataset also includes experiments on asphalt and flooring. All runs were recorded in Forêt Montmorency and on the main campus of Université Laval, Quebec City, Québec, Canada
1 PAPER • 1 BENCHMARK
The code that created this dataset can be seen in https://github.com/nitzanfarhi/SecurityPatchDetection and can be reproduced by running: console python data_collection\create_dataset.py --all -o data_collection\data Notice that this dataset doesn't include the commits' generated data as it is very big. This can be generated by running only : console python data_collection\create_dataset.py --commits -data_collection\data
HASCD (Human Activity Segmentation Challenge Dataset) contains 250 annotated multivariate time series capturing 10.7 h of real-world human motion smartphone sensor data from 15 bachelor computer science students. The recordings capture 6 distinct human motion sequences designed to represent pervasive behaviour in realistic indoor and outdoor settings. The data set serves as a benchmark for evaluating machine learning workflows.
1 PAPER • NO BENCHMARKS YET
MOSAD (Mobile Sensing Human Activity Data Set) is a multi-modal, annotated time series (TS) data set that contains 14 recordings of 9 triaxial smartphone sensor measurements (126 TS) from 6 human subjects performing (in part) 3 motion sequences in different locations. The aim of the data set is to facilitate the study of human behaviour and the design of TS data mining technology to separate individual activities using low-cost sensors in wearable devices.
The sports industry is witnessing an increasing trend of utilizing multiple synchronized sensors for player data collection, enabling personalized training systems with multi-perspective real-time feedback. Badminton could benefit from these various sensors, but there is a scarcity of comprehensive badminton action datasets for analysis and training feedback. Addressing this gap, this paper introduces a multi-sensor badminton dataset for forehand clear and backhand drive strokes, based on interviews with coaches for optimal usability. The dataset covers various skill levels, including beginners, intermediates, and experts, providing resources for understanding biomechanics across skill levels. It encompasses 7,763 badminton swing data from 25 players, featuring sensor data on eye tracking, body tracking, muscle signals, and foot pressure. The dataset also includes video recordings, detailed annotations on stroke type, skill level, sound, ball landing, and hitting location, as well as s
Recorded with a Husky A200 wheeled UGV, the Vulpi 2021 dataset contains 13 min of Inertial Measurement Unit (IMU), motor current, and wheel odometry data, focusing on agricultural terrains. The dataset includes experiments on concrete, a dirt road, a ploughed terrain and an unploughed terrain that were all recorded on an experimental farm in San Cassiano, Lecce, Italy.
The dataset comprises time-series data capturing distinct periodic motions (gaits) of an energetically conservative one-legged hopper. Due to energy conservation, all gaits form a continuous one-dimensional family and undergo bifurcations as the internal energy varies, leading to different motion patterns such as in-place hopping, forward hopping, and backward hopping.
0 PAPER • NO BENCHMARKS YET