19,997 machine learning datasets
19,997 dataset results
In the last two years, millions of lives have been lost due to COVID-19. Despite the vaccination programmes for a year, hospitalization rates and deaths are still high due to the new variants of COVID-19. Stringent guidelines and COVID-19 screening measures such as temperature check and mask check at all public places are helping reduce the spread of COVID-19. Visual inspections to ensure these screening measures can be taxing and erroneous. Automated inspection ensures an effective and accurate screening.
Word embedding is a modern distributed word representations approach widely used in many natural language processing tasks. Converting the vocabulary in a legal document into a word embedding model facilitates subjecting legal documents to machine learning, deep learning, and other algorithms and subsequently performing the downstream tasks of natural language processing vis-à-vis, for instance, document classification, contract review, and machine translation. The most common and practical approach of accuracy evaluation with the word embedding model uses a benchmark set with linguistic rules or the relationship between words to perform analogy reasoning via algebraic calculation. This paper proposes establishing a 1,134 Legal Analogical Reasoning Questions Set (LARQS) from the 2,388 Chinese Codex corpus using five kinds of legal relations, which are then used to evaluate the accuracy of the Chinese word embedding model. Moreover, we discovered that legal relations might be ubiquitous
Object Detection data set created from the engine DeepGTAV, which is based on the video game GTAV. Part of the three data sets proposed in the paper. This data set is motivated from the Cattle dataset with almost the same classes.
Cattle data set, which was introduced in a paper. We (not the authors) created a train-val-test split.
This is an example data set for a hypothetical electronic products supply network.
The Room environment - v0
Microarray gene expression data on 57 bladder samples from 5 batches.
In the actual globalized world, the transportation of goods between any country is something normal. Considering that the protocols in quality and security vary from one country to another, there is a risk with the products that do not comply with the legislation of a country cross the border. In the case of edible products, the importance of avoiding this kind of situation is even higher. Since 1979, European Union members were obligated to register any risk to public health-related with the food and feed that is traded alongside the territory. This information has been registered in a portal called Rapid Alert System for Food and Feed (RASFF). The content of this paper provides a deep description of a set of records that goes from September 1979 to September 2019 both included. Each record represents an issue registered by RASFF workers containing a set of generic features that all issues have in common, and a set of features that are considered details of the issue. The nature of th
Dataset for the Paper "Adversarial Robustness through the Lens of Convolutional Filters".
1.9K Korean Online Hate Speech Comments for Multilabel Classification (Annotated by Three Independent Labelers per Data)
We present a database of multispectral images that were used to emulate the GAP camera. The images are of a wide variety of real-world materials and objects. We are making this database available to the research community. Details of the database can be found in the following publication:
We present a new simulated dataset for pedestrian action anticipation collected using the CARLA simulator. To generate this dataset, we place a camera sensor on the ego-vehicle in the Carla environment and set the parameters to those of the camera used to record the PIE dataset (i.e., 1920x1080, 110° FOV). Then, we compute bounding boxes for each pedestrian interacting with the ego vehicle as seen through the camera's field of view. We generated the data in two urban environments available in the CARLA simulator: Town02 and Town03.
Leaving My Fingerprints: Motivations and Challenges of Contributing to OSS for Social Good -> ICSE 2021 <-
Introduction The China Physiological Signal Challenge 2019 (CPSC 2019) aims to encourage the development of algorithms for challenging QRS detection and heart rate (HR) estimation from short-term single-lead ECG recordings usually with low signal quality and/or abnormal rhythm waveforms.
Introduction Abnormality of cardiac conduction system can induce arrhythmia. Abnormal heart rhythm can lead to other cardiac diseases and complications, and can be life-threatening 1. There are various types of arrhythmias and each type is associated with a pattern, and as such, it is possible to be identified. Arrhythmias can be classified into two major categories. The first category consists of arrhythmias formed by a single irregular heartbeat in electrocardiogram (ECG), herein called morphological arrhythmia, while another category consists of arrhythmias formed by a set of irregular heartbeats in ECG, herein called rhythmic arrhythmias 2. Dynamic electrocardiogram (DCG), like ECG Holter, provides an important way to monitor the incidences of arrhythmias in daily life, facilitating the doctors to check a total number and distribution of arrhythmias in a long time and thus to provide the required therapy to prevent further problems. The 3rd China Physiological Signal Challenge 2020
Introduction The 4th China Physiological Signal Challenge 2021 (CPSC 2021) aims to encourage the development of algorithms for searching the paroxysmal atrial fibrillation (PAF) events from dynamic ECG recordings.
SSD (Sub-slot Dialog) dataset: This is the dataset for the ACL 2022 paper "A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots".
SSD (Sub-slot Dialog) dataset: This is the dataset for the ACL 2022 paper "A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots".
SSD (Sub-slot Dialog) dataset: This is the dataset for the ACL 2022 paper "A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots".
The dataset covers Hindi and Tamil, collected without the use of translation. It provides a realistic information-seeking task with questions written by native-speaking expert data annotators.