The time series segmentation benchmark (TSSB) currently contains 75 annotated time series (TS) with 1-9 segments. Each TS is constructed from one of the UEA & UCR time series classification datasets. We group TS by label and concatenate them to create segments with distinctive temporal patterns and statistical properties. We annotate the offsets at which we concatenated the segments as change points (CPs).
8 PAPERS • 1 BENCHMARK
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
1 PAPER • NO BENCHMARKS YET
The Beijing Traffic Dataset collects traffic speeds at 5-minute granularity for 3126 roadway segments in Beijing between 2022/05/12 and 2022/07/25.
1 PAPER • 1 BENCHMARK
…These signals are preprocessed and segmented, with each segment corresponding to a heartbeat.
8 PAPERS • NO BENCHMARKS YET
…By collecting data in simulations, multi-modal sensor data and precise ground truth labels are obtainable such as the RGB image, depth image, semantic segmentation, change segmentation, camera poses, and
4 PAPERS • 2 BENCHMARKS
…In this dataset, we report the extracted segments used for an analysis of R peak detection algorithms during high intensity exercise. For each subject, 5 segments of 20 s were extracted from the ECG recordings and chosen based on different phases of the maximal exercise test (i.e., before and after the so-called second ventilatory threshold seg1 --> [VT2-50,VT2-30] seg2 --> [VT2+60,VT2+80] seg3 --> [VO2max-50,VO2max-30] seg4 --> [VO2max-10,VO2max+10] seg5 --> [VO2max+60,VO2max+80] The R peak locations were manually annotated in all segments Only segment 5 of subject 9 could not be annotated since there was a problem with the input signal. So, the total number of segments extracted were 20 * 5 - 1 = 99. Format of the extracted dataset The dataset is divided in two main folders: The folder `ecg_segments/` contains the ECG signals saved in two formats, `.csv` and `.mat`.
Automated leaf segmentation is a challenging area in computer vision.
2 PAPERS • NO BENCHMARKS YET
…It provides data for the analysis of the complete inertial pose pipeline, from raw measurements, to sensor-to-segment calibration, multi-sensor fusion, skeleton kinematics, to the complete human pose.
…To curate this collection, we sifted through thousands of hours of driving data from our fleet of self-driving test vehicles to find the most challenging segments.
14 PAPERS • NO BENCHMARKS YET
…The presented work aims to study the potential of automated ventricular dimension estimation through heart segmentation in medaka.
0 PAPER • NO BENCHMARKS YET
…The dataset can be used for activity recognition and intensity estimation, while developing and applying algorithms of data processing, segmentation, feature extraction and classification.
149 PAPERS • 1 BENCHMARK
…Activity labels Annotations of the experimental task activity the subject performed throughout the session, including instruction, rest, and active experiment segments. We label each segment of the active experiment as one of four possible n-back working memory intensity levels (0-back, 1-back, 2-back, or 3-back).