LabPics Chemistry Dataset Dataset for computer vision for materials segmentation and classification in chemistry labs, medical labs, and any setting where materials are handled inside containers. In addition to instance segmentation maps, the dataset also includes semantic segmentation maps that give each pixel in the image all the classes to which it belongs.
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BPCIS is collection of 364 bacterial phase contrast images and corresponding label matrices for instance segmentation. Labels were made according to fluorescence channels where possible.
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…It has been utilized towards the development of models able to: (i) extract clinically informative respiratory indicators from regular breathing records, and (ii) identify cough, breath and voice segments
…Image based benchmark datasets have driven development in computer vision tasks such as object detection, tracking and segmentation of agents in the environment.
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…Une large base de données pour la détection de segments de vidéos TV.
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…Segmented transcripts are also provided. The corpus aims to support researchers in speech recognition, machine translation, voiceprint recognition, and other speech-related fields.
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…The GVLM dataset can be used to develop and evaluate machine/deep learning models for change detection, semantic segmentation and landslide extraction.
…Experiments on semantic segmentation datasets show that using the acquired data to supplement real-world images significantly increases accuracy and that the acquired data enables reducing the amount of
…Sample videos of the JIGSAWS tasks can be downloaded from the official webpage. manual annotations including: gesture (atomic surgical activity segment labels). skill (global rating score using modified
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…While most of the research efforts in this domain are focused on detecting high-quality deepfake images and videos, only a few works address the problem of the localization of small segments of audio-visual
…The segmentation allows one to make a quantification of the MI, in absolute value (mm3) or percentage of the myocardium.
…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.
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…We segmented these images using Removebg application, and computed the UV coordinates from DensePose. Download TikTok Dataset: Please use the dataset only for the research purpose.
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…In order to ease multitask learning, we provide a pairing of 2D instance segments with 3D bounding boxes.
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…AVA Speech densely annotates audio-based speech activity in AVA v1.0 videos, and explicitly labels 3 background noise conditions, resulting in ~46K labeled segments spanning 45 hours of data.
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…Subtask 2: Stroke Classification: Participants are required to build a classification system that automatically labels video segments according to a performed stroke.
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…The presented work aims to study the potential of automated ventricular dimension estimation through heart segmentation in medaka.
…The main objective of this dataset is to create the basis for experimenting with suitable solutions to give a reliable answer to the above questions, or to propose models capable of producing dynamic segmentation
The OCTAGON dataset is a set of Angiography by Octical Coherence Tomography images (OCT-A) used to the segmentation of the Foveal Avascular Zone (FAZ).
There exist previous works [6, 10] that constructed referring segmentation datasets for videos. Each video has pixel-level instance segmentation annotation at every 5 frames in 30-fps videos, and their durations are around 3 to 6 seconds.
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…This sub-dataset comes from the 10th Medical Segmentation Decathlon14. To attain more slices containing the spine, we select the task03_liver dataset consisting of 201 cases.
…The dataset can be used for activity recognition and intensity estimation, while developing and applying algorithms of data processing, segmentation, feature extraction and classification.
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…Overall this dataset covers a wide range of perception related tasks such as loop closure detection, semantic segmentation, visual odometry estimation, global localization, scene flow estimation and behavior
…The images in the dataset are formatted according to the following protocol: CASE NUMBER | FILE TYPE (LOC OR SEG) | FILE EXTENSION | where loc is the original image and seg is the associated segmentation
…Mixtures were created by randomly selecting event instance and from it, randomly, a segment of length 3-15 seconds. Between events, random length silent region was introduced.
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…These cells are selected from the epithelial area -- a region of interest that has been explicitly segmented by experts.
…The floorplans are annotated with room outline polygons, doors/windows as line segments, object-icons as axis-aligned bounding boxes, room-door-room connectivity graphs, and photo-room assignments.
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…Second, answer groundings enable segmenting the relevant content from the background.
…human-centric synthetic data generator PeopleSansPeople which contains simulation-ready 3D human assets, a parameterized lighting and camera system, and generates 2D and 3D bounding box, instance and semantic segmentation
…Each subfolder also contains a "siginfo.csv" file specifying the respective simulation run for the P wave and the QRST segment that was used to synthesize the 10 second ECG segment.
…Squats Bird Dogs Supermans Bicycle Crunches Leg Raises Front Raises (with dumbbells) Overhead Press (with dumbbells) Annotations The dataset includes the following annotations: Bounding boxes Segmentation
…These questions are divided into four groups: Humanities Languages Sciences Mathematics The dataset I found contains only the textual part of the objective section, segmented into individual questions
… 'bridge_answers': [{'label': 'passage', 'length': 14, 'offset': 300, 'segment': 'Simon McBurney'}], 'main_answers': [{'label': 'passage', 'length': 9, 'offset': 47, 'segment': Cambridge'}], 'episode
The goal of the Automated Cardiac Diagnosis Challenge (ACDC) challenge is to: compare the performance of automatic methods on the segmentation of the left ventricular endocardium and epicardium as the
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The RITE (Retinal Images vessel Tree Extraction) is a database that enables comparative studies on segmentation or classification of arteries and veins on retinal fundus images, which is established based
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Our project (STPLS3D) aims to provide a large-scale aerial photogrammetry dataset with synthetic and real annotated 3D point clouds for semantic and instance segmentation tasks.
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…Atlas was created based on the original MRM NeAt mouse brain atlas (template images reoriented and bias-corrected, left/right structure label seperated, and 4th ventricle manual segmentation added). Citation If you use the segmented brain structure, or use the atlas along with the automatic mouse brain MRI segmentation tools, we ask you to kindly cite the following papers: Ma D, Cardoso MJ, Modat
…Ground Truth Annotations: These include 6DoF camera trajectory, 3D floor plan, 2D instance segmentation, and 2D depth map¹1.
…"Multimodal analysis for identification and segmentation of moving-sounding objects."IEEE Transactions on Multimedia 15.2 (2013): 378-390. 3 Li, Kai, Jun Ye, and Kien A. Hua.
…Thus, accurate identification and segmentation of nuclei of multiple cell-types is important for AI enabled characterization of tumor and its microenvironment.
…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).
…The code for stain translation is available at https://github.com/nadeemlab/DeepLIIF and the code for performing interactive deep learning whole-cell/nuclear segmentation is available at https://github.com
…Segmentation masks Bounding boxes For the full description of labels and metadata, check out the README.
…Segments Info | Genres | Tokens, millions | % | |------------------|------------------|-----| | News | 92 | 1.5 | | Literary Texts | 4605 | 76 | |
…The localization of each field is not available in such a way that this dataset encourages research on segmentation-free systems for information extraction.
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…✔️ Definition To Detect and Classify Brain Tumor using, CNN and TL; as an asset of Deep Learning and to examine the tumor position(segmentation).
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…"COVID-19 CT Lung and Infection Segmentation Dataset," Zenodo, Apr, vol. 20, 2020. "COVID-19." 2020. [Online] http://medicalsegmentation.com/covid19/ [Accessed 23 December, 2020].
…They include body height, weight, and segment lengths measured before the beginning of a recording session.