large classification datasets

Despite the ability to detect the structures visually on the images, this method would be time-consuming on large datasets, thus limiting the possibilities to perform studies of the structures properties over more than a few … This is a total of 22 points that are considered outliers according to cook’s distance test. The dataset is 20 times larger than the existing largest dataset for text in videos. With over 850,000 building polygons from six different types of natural disaster around the world, covering a total area of over 45,000 square kilometers, the xBD dataset is one of the largest and highest quality public datasets of annotated high-resolution satellite imagery. The Replica Dataset is a dataset of high quality reconstructions of a variety of indoor spaces. Dataset is built upon the TV drama "Another Miss Oh" and it contains 16,191 QA pairs from 23,928 various length video clips, with each QA pair belonging to one of four difficulty levels. A dataset for yoga pose classification with 3 level hierarchy based on body pose. Using drones and traffic cameras, trajectories were captured from different countries, including the US, Germany, China and other countries. All datasets are comprised of tabular data and no (explicitly) missing values. Drop them. 2.5) What is our response/target variable? Attribution No Derivatives 4.0 International (CC BY ND 4.0) - WebGraph – A framework to study the web graph. mice automatically skips those columns and lets us know of the issue. ShareAlike - if you make changes, you must distribute your contributions. 100,000 high-resolution images from all over the world with bounding box annotations of over 300 classes of traffic signs. This dataset is generated by our DG-Net and consists of 128,307 images (613MB), about 10 times larger than the training set of original Market-1501. Each video is from the BDD100K dataset. # local outlier factor for imbalanced classification from numpy import vstack from sklearn.datasets import make_classification from sklearn.model_selection import train_test_split from sklearn.metrics import f1_score from sklearn.neighbors import LocalOutlierFactor # make a prediction with a lof model def lof_predict(model, trainX, testX): # create one large dataset … Class imbalance? The VisDrone2019 dataset is collected by the AISKYEYE team at Lab of Machine Learning and Data Mining , Tianjin University, China. The dataset consists of 13,215 task-based dialogs, including 5,507 spoken and 7,708 written dialogs created with two distinct procedures. In big organizations the datasets are large and training deep learning text classification models from scratch is a feasible solution but for the majority of real-life problems your dataset is small and if you want to build your machine learning model you need to be smart. The data need to be attributes based, that is it uses real, integer, or nominal values. Unlike bounding-boxes, which only identify regions in which an object is located, segmentation masks mark the outline of objects, characterizing their spatial extent to a much higher level of detail. Includes 15000 annotated videos and 4M annotated images. You are free to: This challenge builds upon a series of successful challenges on large-scale hierarchical text classification. Then, they were divided into 590,326 non-overlapping image patches. The links were then distributed to several machines in parallel for download, and all web pages were extracted using the newspaper python package. KeypointNet is a large-scale and diverse 3D keypoint dataset that contains 83,231 keypoints and 8,329 3D models from 16 object categories, by leveraging numerous human annotations, based on ShapeNet models. This is the first public dataset to focus on real world driving data in snowy weather conditions. PandaSet combines Hesai’s best-in-class LiDAR sensors with Scale AI’s high-quality data annotation. 2.9) Check for missing values. Captured at different times (day, night) and weathers (sun, cloud, rain). It contains photos of litter taken under diverse environments, from tropical beaches to London streets. Apache License 2.0 - The dataset combines visual, textual and temporal coherence reasoning together with knowledge-based questions, which need of the experience obtained from the viewing of the series to be answered. Dataset includes more than 40,000 frames with semantic segmentation image and point cloud labels, of which more than 12,000 frames also have annotations for 3D bounding boxes. We are releasing this dataset publicly to aid the research community in making advancements in machine perception and self-driving technology. There are 300 frames in each video sequence. You are free to: We provide 217,308 annotated images with rich character-centered annotations. It offers data from four WUXGA cameras, two 3D LiDARs, inertial measurement unit, infrared camera and especially differential RTK GNSS receiver with centimetre accuracy which, to the best knowledge of the authors, is not available from any other public dataset so far. For simplicity, assume X is count-able, and consider only binary labels Y = {−1,+1}. Human Activity Knowledge Engine (HAKE) aims at promoting the human activity/action understanding. The … Dataset of Human Eye Fixation over Crowd Videos. The datasets is made up of over 260 million laser scanning points labelled into 100,000 objects. To do that, we first store the column names being careful not to store the set column name (we need it). In this work, we construct a large scale logo dataset, Logo-2K+, which covers a diverse range of logo classes from real-world logo images. PedX is a large-scale multi-modal collection of pedestrians at complex urban intersections. The collected videos have a creative-commons license. Authors Lior Shamir 1 , Carol Yerby 1 , Robert Simpson 2 , Alexander M … SEN12MS is a dataset consisting of 180,748 corresponding image triplets containing Sentinel-1 dual-pol SAR data, Sentinel-2 multi-spectral imagery, and MODIS-derived land cover maps. It is constructed from web images and consists of 82 yoga poses. The current COVIDx dataset is constructed from other open source chest radiography datasets. You are free to: Recommender Systems Datasets: This dataset repository contains a collection of recommender systems datasets that have been used in the research of Julian McAuley, an associate professor of the computer science department of UCSD. A list of datasets for skin image analysis, from the 'Visual Diagnosis of Dermatological Disorders: Human and Machine Performance' paper. We have now both our training and testing data sets ready for modelling. This will take care of class imbalance. DBSCAN? Anything strange? The scenes may contain 4k head counts with over 100× scale variation. Attribution - you must give approprate credit, Get the data here. The large variation in call types of these species makes it challenging to categorize them. Again, we have 8.4% missing values. Missing values are denoted by “na”. PANDA provides enriched and hierarchical ground-truth annotations, including 15,974.6k bounding boxes, 111.8k fine-grained attribute labels, 12.7k trajectories, 2.2k groups and 2.9k interactions. Regarding the former, an extra row EE_par is added having the same AUC-value as EE(\(S=15\)). Here’s a nice explanation of how mice works. We assume there exists an unknown target distribution … If you run that code and look at each row, you will notice there are some features that still have missing values. 4703 CXR of COVID19 patients. In addition, we provide 1000 Deepfakes models to generate and augment new data. One of them is our set column (the one we used to combine the two sets into one), so we don’t worry about that one. Originally prepared for a machine learning class, the News and Stock dataset is great for binary classification tasks. A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning. This project introduces a novel video dataset, named HACS (Human Action Clips and Segments). Each image patch was annotated by the multiple land-cover classes (i.e., multi-labels) that were provided from the CORINE Land Cover database of the year 2018. A large-scale vehicle ReID dataset in the wild (VERI-Wild) is captured from a large CCTV surveillance system consisting of 174 cameras across one month (30× 24h) under unconstrained scenarios. The WiderPerson dataset is a pedestrian detection benchmark dataset in the wild, of which images are selected from a wide range of scenarios, no longer limited to the traffic scenario. TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs. Real data correspond to processed versions of sequences acquired from real world. 313 object classes with 113 overlapping ImageNet, JRDB is the largest benchmark data for 2D-3D person tracking, including: Over 60K frames (67 minutes) sensor data captured from 5 stereo camera and two LiDAR sensors, 54 sequences from different locations, during day and night time, indoors and outdoors in a university campus environment. If we didn’t do that, the presence of na in each column would automatically result in them being categorized as character type. This means we have 8.3% o missing values in average in each column. We did it as a parameter set within caret’s trainControl so I’m not showing any details of that, but by doing it, we have improved our ability to predict the positive class (in this case “neg”) in detriment of just looking to maximize accuracy. A new dataset recorded in Brno, Czech Republic. A diverse street-level imagery dataset with bounding box annotations for detecting and classifying traffic signs around the world. The languages of TyDi QA are diverse with regard to their typology -- the set of linguistic features that each language expresses -- such that we expect models performing well on this set to generalize across a large number of the languages in the world. A large dataset of almost two million annotated vehicles Uni-variate or Multi-variate? The dataset contains rigorously annotated and validated videos, questions and answers, as well as annotations for the complexity level of each question and answer. A permissive license whose main conditions require preservation of copyright and license notices. This is very important since our prediction errors can result in unnecessary spending by the company. A2D2 is around 2.3 TB in total. ShareAlike - if you make changes, you must distribute your contributions. The datasets contain social networks, product reviews, social circles data, and question/answer data. Large video dataset for action classification. ImageMonkey is a free, public open source dataset. Agriculture-Vision: a large-scale aerial farmland image dataset for semantic segmentation of agricultural patterns. In order to derive useful biological knowledge from this large database, a variety of supervised classification algorithms were … The dataset is divided into train and test split and There are 50000 images in the training dataset … Positive class consists of component failures for a specific component of the APS system. The largest production recognition dataset containing 10,000 products frequently bought by online customers in The dataset is multi-class, multi-label and hierarchical. A new dataset for natural language based fashion image retrieval. The third is a set of HD maps of several neighborhoods in Pittsburgh and Miami, to add rich context for all of the data mentioned above. Attribution 4.0 International (CC BY 4.0) - MIT - You are free to: use, copy, modify, merge, publish, distribute, sublicense, and/or sell KnowIT VQA is a video dataset with 24,282 human-generated question-answer pairs about The Big Bang Theory. The dataset contains 28 classes including classes distinguishing non-moving and moving objects. The Unsupervised Llamas dataset was annotated by creating high definition maps for automated driving including lane markers based on Lidar. NonCommercial - you may not use the material for commercial purposes. A New Dataset Size Reduction Approach for PCA-Based Classification in OCR Application, Mathematical Problems in Engineering, Volume 2014, Article ID 537428, 14 pages. It consists of 9,980 8-way multiple-choice questions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences. ObjectNet is a large real-world test set for object recognition with control where object backgrounds, rotations, and imaging viewpoints are random. Under CC license. Our features present more than 8% missing values in average. The Celeb-DF dataset includes 408 original videos collected from YouTube with subjects of different ages, ethic groups and genders, and 795 DeepFake videos synthesized from these real videos. Dataset contains 104 K+ images, 154 activity classes, 677 K+ human instances. Share - copy and redistribute, The diverse content refers to different crowd activities under three distinct categories - Sparse, Dense Free Flowing and Dense Congested. An update to the popular All the News dataset published in 2017. CLUE is an open-ended, community-driven project that brings together 9 tasks spanning several well-established single-sentence/sentence-pair classification tasks, as well as machine reading comprehension, all on original Chinese text. >2 hours raw videos, 32,823 labelled frames,132,034 object instances. Abstract—In this paper a new algorithm, OKC classifier is proposed that is a hybrid of One-Class SVM, k-Nearest Neighbours and CART algorithms. Maruthi Rohit Ayyagari . The Waymo Open Dataset currently contains lidar and camera data from 1,000 segments (20s each): 1,000 segments of 20s each, collected at 10Hz (200,000 frames) in diverse geographies and conditions, Labels for 4 object classes - Vehicles, Pedestrians, Cyclists, Signs, 12M 3D bounding box labels with tracking IDs on lidar data, 1.2M 2D bounding box labels with tracking IDs on camera data... A comprehensive, large-scale dataset featuring the raw sensor camera and LiDAR inputs as perceived by a fleet of multiple, high-end, autonomous vehicles in a bounded geographic area. You are free to: In this study, sounds reco … Classification of large acoustic datasets using machine learning and crowdsourcing: application to whale calls J Acoust Soc Am. It contains 31 daily living activities and 18 subjects. I’ll use caretEnsemble’s caretList()to train both at the same time and with the same resampling . Are they OK? Flexible Data Ingestion. We can see above that the average number of missing values per feature is 5,000 out of 60,000 samples. If not, convert. Computational Use of Data Agreement (C-UDA): A high resolution camera was used to acquire images at a size of 6000x4000px (24Mpx). for training and evaluating object detection methods. Climate datasets belong to the Spatial Big Data domain; they are very large, and hence traditional methods of processing them are not adequate. horizontal, multi-oriented, and curved) have high number of existence in the dataset, which makes it an unique dataset. We leverage a simulated driving environment to create a dataset for anomaly segmentation, which we call StreetHazards. I am looking for a large dataset to use for classification. Summary statistics. Human-centric Video Analysis in Complex Events. The data is automatically generated according to expert-crafted grammars. All videos are at 720p resolution and 30 Hz frame rate. There are 49 real sequences and 49 unreal sequences that do not include any specific challenge. COVID19 severity score assessment project and database. PandaSet features data collected using a forward-facing LiDAR with image-like resolution (PandarGT) as well as a mechanical spinning LiDAR (Pandar64). In addition, all the data are precisely timestamped with sub-millisecond precision to allow wider range of applications. A semantic map provides context to reason about the presence and motion of the agents in the scenes. (check it!). Resolution of 1276 x 717 pixels. The Exclusively Dark (ExDARK) dataset is a collection of 7,363 low-light images from very low-light environments to twilight (i.e 10 different conditions) with 12 object classes (similar to PASCAL VOC) annotated on both image class level and local object bounding boxes. summary_df_t_2 %>% summarise(Min = mean(Min. Total_cost = Cost_1 * No_Instances + Cost_2 * No_Instances. We’ll have to deal with them and there’s a specific section for that afterwards. The attribute names of the data have been anonymized for proprietary reasons. The Oxford Radar RobotCar Dataset is a radar extension to The Oxford RobotCar Dataset. The additional, partially annotated dataset contains 47,547 images with more than 80,000 signs that are automatically labeled with correspondence information from 3D reconstruction. MoVi is the first human motion dataset to contain synchronized pose, body meshes and video recordings. The CDLA agreement is similar to permissive open source licenses in that the publisher of data allows anyone to use, modify and do what they want with the data with no obligations to share any of their changes or modifications. Due to the size of the data, we will train a Logistic Regression model and a Naive Bayes model. Specifically we want to avoid type 2 errors (cost of missing a faulty truck, which may cause a breakdown). DoQA is a dataset for accessing Domain Specific FAQs via conversational QA that contains 2,437 information-seeking question/answer dialogues (10,917 questions in total) on three different domains: cooking, travel and movies. An Iterative Classification Scheme for SanitizingLarge-Scale DatasetsIEEE 2017-18S/W: Java , JSP, MySQL The datasets’ positive class consists of component failures for a specific component of the APS system. The video sequences in the CURE-TSD dataset are grouped into two classes: real data and unreal data. Facebook, Microsoft, Amazon Web Services, and the Partnership on AI have created the Deepfake Detection Challenge to encourage research into deepfake detection. The imagery depicts more than 20 houses from nadir (bird's eye) view acquired at an altitude of 5 to 30 meters above ground. Real . The CADC dataset aims to promote research to improve self-driving in adverse weather conditions. These images are paired with "ground truth" annotations that segment each of the buildings. With this summary data frame we will also calculate the mean quartiles for all the data. Filter By Classification Regression. Dataset for text in driving videos. Ionosphere Dataset. Make learning your daily ritual. These operations require a much more comprehensive understanding of the content of paragraphs than what was necessary for prior datasets. The training set contains 400 publicly available images and the test set is made up of 200 private images. Abstract. Here we see that some features were tagged as constant or collinear. Open Images V6 expands the annotation of the Open Images dataset with a large set of new visual relationships, human action annotations, and image-level labels. Can only be used for research and educational purposes. The rest of them are mainly collinear variables and one constant variable. The dataset can be used for landmark recognition and retrieval experiments. More than 220,000 Attribution - you must give approprate credit, Sonar Dataset. This distribution was created by Aaron Gokaslan and Vanya Cohen of Brown University. It also includes localized narratives annotations for the full 123k images of the COCO dataset. Each reconstruction has clean dense geometry, high resolution and high dynamic range textures, glass and mirror surface information, planar segmentation as well as semantic class and instance segmentation. ETH-XGaze, consisting of over one million high-resolution images of varying gaze under extreme head poses. Check all of them. Open WebText – an open source effort to reproduce OpenAI’s WebText dataset. Binary or Multi-class? Commercial use is prohibited. Unlike previous fashion datasets, we provide natural language annotations to facilitate the training of interactive image retrieval systems, as well as the commonly used attribute based labels. I bet that with some more work we can get very close to the best 3 contestants: Hands-on real-world examples, research, tutorials, and cutting-edge techniques delivered Monday to Thursday. Share - copy and redistribute, This dataset contains 2.7 million articles from 26 different publications from January 2016 to April 1, 2020. A data scientist may look at a 45–55 split dataset and judge that this is close enough that measures do not need to be taken … A*3D dataset is a step forward to make autonomous driving safer for pedestrians and the public in the real world. The the remaining documents were tokenized, and documents with fewer than 128 tokens were removed. Smarthome has been recorded in an apartment equipped with 7 Kinect v1 cameras. QMUL-OpenLogo contains 27,083 images from 352 logo classes, built by aggregating and refining 7 existing datasets and establishing an open logo detection evaluation protocol. 2.2) What type of problem is it? Contains over 100,000 images. Full citation list of the datasets contained: {The CommitmentBank}: Investigating projection in naturally occurring discourse, Choice of plausible alternatives: An evaluation of commonsense causal reasoning, Looking beyond the surface: A challenge set for reading comprehension over multiple sentences, The {PASCAL} recognising textual entailment challenge, The second {PASCAL} recognising textual entailment challenge, The third {PASCAL} recognizing textual entailment challenge, The Fifth {PASCAL} Recognizing Textual Entailment Challenge, {WiC}: The Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations, The {W}inograd schema challenge. 09/14/2016 ∙ by T. Nathan Mundhenk, et al. 600k images There are specific cost associated to type 1 errors and type 2 errors, which requires that we minimize type 2 errors. Cifar 10 dataset is used for image classification. The datasets’ positive class consists of component failures for a specific component of the APS system. Our dataset comprises 1000 video clips of driving without any bias towards text and with annotations for text bounding boxes and transcriptions in every frame. The Smartphone Image Denoising Dataset (SIDD), of ~30,000 noisy images from 10 scenes under different lighting conditions using five representative smartphone cameras and generated their ground truth images. This will enable us to calculate some new statistics, specifically related to missing values, which as you will see, is another big issue of this data. SciTLDR includes at least two high-quality TLDRs for each paper. Objects365 is a brand new dataset, designed to spur object detection research with a focus on diverse objects in the Wild: There is no additional information we could use. Web Data Commons – Hyperlink Graph, generated from the Common Crawl dataset. It consists of 152.5K QA pairs from 21.8K video clips, spanning over 460 hours of video. We introduce RISE, the first large-scale video dataset for Recognizing Industrial Smoke Emissions. Moreover, there are 49 synthesized video sequences processed with 11 different types of effects and 5 different challenge levels. test_data <- read.csv("aps_failure_test_set.csv". It consists of both single numerical counters and histograms consisting of bins with different conditions. DDAD (Dense Depth for Autonomous Driving) is a new autonomous driving benchmark from TRI (Toyota Research Institute) for long range (up to 250m) and dense depth estimation in challenging and diverse urban conditions. This dataset is a labeled subset of 80 million tiny images dataset that was collected by Alex Krizhevsky, Vinod Nair and Geoffrey Hinton. In order to do that we just filter the data frame using our set column. It is a binary classification problem with multiple features. Classification or Regression? It contains 12,102 questions with one correct answer and four distractor answers. We need to predict the type of system failure. Our dataset has been built by taking 29,000+ photos of 69 different models over the last 2 years in our studio. The dataset contains data from several sources, check the links on the website for individual licenses. Dataset contains 9 hours of motion capture data, 17 hours of video data from 4 different points of view (including one hand-held camera), and 6.6 hours of IMU data. Break is a question understanding dataset, aimed at training models to reason over complex questions. Under the following terms: ClarQ: A large-scale and diverse dataset for Clarification Question Generation. These images are manually labeled and segmented according to a hierarchical taxonomy to train and evaluate object detection algorithms. The Total-Text consists of 1555 images with more than 3 different text orientations: Horizontal, Multi-Oriented, and Curved, one of a kind. CLUE: A Chinese Language Understanding Evaluation Benchmark. Box-plots. Social-IQ brings novel challenges to the field of artificial intelligence which sparks future research in social intelligence modeling, visual reasoning, and multimodal question answering. Class is totally imbalanced. AU-AIR dataset is the first multi-modal UAV dataset for object detection. A database of COVID-19 cases with chest X-ray or CT images. Each log in the dataset is time-stamped and contains raw data from all the sensors, calibration values, pose trajectory, ground truth pose, and 3D maps. ShareAlike - if you make changes, you must distribute your contributions. 45M frames of video Video, images, text Classification, action detection 2013 Y. Jiang et al. In that sense, I came across this dataset in the UCI Machine Learning Repository which I intend to use. A Large-Scale Logo Dataset for Scalable Logo Classification. Average rank AUC versus average rank Time (see Table 9) across the large datasets from Table 2 (CRF and Bank). A dataset with16,756 chest radiography images across 13,645 patient cases. Share - copy and redistribute, Attribution-NonCommercial-NoDerivs International - BIMCV-COVID19+: a large annotated dataset of RX and CT images of COVID19 patients. This version of the dataset contains approximately 5 million images, split into 3 sets of images: train, index and test. Impute them? The benchmark dataset consists of 288 video clips formed by 261,908 frames and 10,209 static images, captured by various drone-mounted cameras, covering a wide range of aspects including location (taken from 14 different cities separated by thousands of kilometers in China), environment (urban and country), objects (pedestrian, vehicles, bicycles, etc. So now I’ve decided to take this from easy difficulty to normal difficulty. I’m not looking here to win the contest but to have an acceptable scoring just to demonstrate. 50,000 image test set, same as ImageNet, with controls for rotation, background, and viewpoint. Our dataset exceeds the existing task-oriented dialogue corpora in scale, while also highlighting the challenges associated with building large-scale virtual assistants. Synthinel also has a subset dataset called Synth-1, which contains 1,640 images spread across six styles. However the datasets above does not meet the 'large' requirement. The flight altitude was mostly around 300m and the total journey was performed in 41 flight path strips. At the time of publishing of the paper, it contains recordings of more than 350 km of rides in varying environments. After data cleaning and annotation, 416,314 vehicle images of 40,671 identities are collected.

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