19,997 machine learning datasets
19,997 dataset results
The dataset is for research on the label distribution shift between multiple domain adaptations. We use Cl, Pr, and Rw to resample two reverse long-tailed distributions and one Gaussian d for each of them for BTDA with label shift.
Workshop Tools Dataset Motivated by the need for a dataset that also includes inertial information about the objects, we contribute the following dataset. It contains 20 common workshop tools, and for each object: - a watertight triangular surface mesh; - a synthetic colored surface point-cloud; - ground truth inertial parameters; - ground truth part-level segmentation; and - a grasping reference frame.
This dataset is based on FB15k237 and a pre-trained language-model-based KGE. The main task is to add the new knowledge that the pre-trained model didn't see in the previous training stage. The model can be downloaded from here.
This dataset is based on WN18RR and a pre-trained language-model-based KGE. The main task is to correct the wrong knowledge stored in the pre-trained model and replace the incorrect entities with alternative entities. The model can be downloaded from here.
This dataset is based on WN18RR and a pre-trained language-model-based KGE. The main task is to add the new knowledge that the pre-trained model didn't see in the previous training stage. The model can be downloaded from here.
A Rich Annotated Mandarin Conversational (RAMC) Speech Dataset, including 180 hours of Mandarin Chinese dialogue, 150, 10 and 20 hours for the training set, development set and test set respectively. It contains 351 multi-turn dialogues, each of which is a coherent and compact conversation centered around one theme.
This repository contains a dataset and machine learning algorithms to detect poisoned water from clean water via using equivalent Smartphone embedded Wi-Fi CSI data.
This is the set of graphs used in the PACE 2022 challenge for computing the Directed Feedback Vertex Set, from the Heuristic track. It consists of 200 labelled directed graphs. The graphs are mostly not symmetric (an edge form u->v does not imply an edge from v->u), although some are symmetric. The graph labels are integers ranging from 1 to N.
AfriSenti is the largest sentiment analysis dataset for under-represented African languages, covering 110,000+ annotated tweets in 14 African languages (Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yoruba).
This paper details the design of an autonomous alignment and tracking platform to mechanically steer directional horn antennas in a sliding correlator channel sounder setup for 28 GHz V2X propagation modeling. A pan-and-tilt subsystem facilitates uninhibited rotational mobility along the yaw and pitch axes, driven by open-loop servo units and orchestrated via inertial motion controllers. A geo-positioning subsystem augmented in accuracy by real-time kinematics enables navigation events to be shared between a transmitter and receiver over an Apache Kafka messaging middleware framework with fault tolerance. Herein, our system demonstrates a 3D geo-positioning accuracy of 17 cm, an average principal axes positioning accuracy of 1.1 degrees, and an average tracking response time of 27.8 ms. Crucially, fully autonomous antenna alignment and tracking facilitates continuous series of measurements, a unique yet critical necessity for millimeter wave channel modeling in vehicular networks. The
This dataset contains a collection of 131 X-ray CT scans of pieces of modeling clay (Play-Doh) with various numbers of stones inserted, retrieved in the FleX-ray lab at CWI. The dataset consists of 5 parts. It is intended as raw supplementary material to reproduce the CT reconstructions and subsequent results in the paper titled "A tomographic workflow enabling deep learning for X-ray based foreign object detection". The dataset can be used to set up other CT-based experiments concerning similar objects with variations in shape and composition.
This dataset contains a collection of 235800 X-ray projections of 131 pieces of modeling clay (Play-Doh) with various numbers of stones inserted. The dataset is intended as an extensive and easy-to-use training dataset for supervised machine learning driven object detection. The ground truth locations of the stones are included.
LoT-insts contains over 25k classes whose frequencies are naturally long-tail distributed. Its test set from four different subsets: many-, medium-, and few-shot sets, as well as a zero-shot open set. To our best knowledge, this is the first natural language dataset that focuses on this long-tailed and open classification problem.
This dataset was presented as part of the ICLR 2023 paper ๐ ๐ง๐ณ๐ข๐ฎ๐ฆ๐ธ๐ฐ๐ณ๐ฌ ๐ง๐ฐ๐ณ ๐ฃ๐ฆ๐ฏ๐ค๐ฉ๐ฎ๐ข๐ณ๐ฌ๐ช๐ฏ๐จ ๐๐ญ๐ข๐ด๐ด-๐ฐ๐ถ๐ต-๐ฐ๐ง-๐ฅ๐ช๐ด๐ต๐ณ๐ช๐ฃ๐ถ๐ต๐ช๐ฐ๐ฏ ๐ฅ๐ฆ๐ต๐ฆ๐ค๐ต๐ช๐ฐ๐ฏ ๐ข๐ฏ๐ฅ ๐ช๐ต๐ด ๐ข๐ฑ๐ฑ๐ญ๐ช๐ค๐ข๐ต๐ช๐ฐ๐ฏ ๐ต๐ฐ ๐๐ฎ๐ข๐จ๐ฆ๐๐ฆ๐ต.
PIE stands for Performance Improving Code Edits. PIE contains trajectories of programs, where a programmer begins with an initial, slower version and iteratively makes changes to improve the programโs performance.
The Robot Tracking Benchmark (RTB) is a synthetic dataset that facilitates the quantitative evaluation of 3D tracking algorithms for multi-body objects. It was created using the procedural rendering pipeline BlenderProc. The dataset contains photo-realistic sequences with HDRi lighting and physically-based materials. Perfect ground truth annotations for camera and robot trajectories are provided in the BOP format. Many physical effects, such as motion blur, rolling shutter, and camera shaking, are accurately modeled to reflect real-world conditions. For each frame, four depth qualities exist to simulate sensors with different characteristics. While the first quality provides perfect ground truth, the second considers measurements with the distance-dependent noise characteristics of the Azure Kinect time-of-flight sensor. Finally, for the third and fourth quality, two stereo RGB images with and without a pattern from a simulated dot projector were rendered. Depth images were then recons
We build what we name the Nearly-Nested Image Datasets (NNID) such that each dataset owns images of the same dimension, and each dataset is issued from a cropped version of the images belonging to the dataset with the biggest dimensions. This last dataset is named mother dataset and the images are named mother images.
A simulated dataset built in Unreal Engine 4 with AirSim. Designed for visual point cloud change detection. Including GT point clouds before changes and after changes. Besides, 4 trajectories with stereo camera and IMU data are recorded for change detection task.
Press Briefing Claim Dataset The dataset contains a total of 53 press briefings from a time span of over four years (2017-2021). While, on average, one press briefing per month is held, the distribution is highly skewed towards recent years.
The field of biomechanics is at a turning point, with marker-based motion capture set to be replaced by portable and inexpensive hardware, rapidly improving markerless tracking algorithms, and open datasets that will turn these new technologies into field-wide team projects. To expedite progress in this direction, we have collected the CMU Panoptic Dataset 2.0, which contains 86 subjects captured with 140 VGA cameras, 31 HD cameras, and 15 IMUs, performing on average 6.5 min of activities, including range of motion activities and tasks of daily living.