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120 results for “Gloves”

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zenodo44/100

FORTH_GLOVES_09/30/22

Documentation material from the Mastic pilot of the Mingei project

opencc-by-sa-4.0Sep 2022View details →
zenodo44/100

MC-hands-1M: A glove-wearing hand dataset for pose estimation

<p>We introduce&nbsp;MC-hands-1M, a synthetic glove-wearing hand dataset for pose estimation. In the zip folder, there exist two subfolders: one containing roughly 750K images (Big set) and another with 250K images (Small set)&nbsp;along with the 2D camera plane and 3D world ground truth data of the corresponding poses. Each set is organized in folders named as Rendered View X, representing a specific camera in the 3D space with a fixed rotation and location. In each of those folders, there exist a json file containing corresponding data for the camera (location, rotation, intrinsics' matrix and images' relative paths) along with the aforementioned ground truth per image (pose). For each of those views, there exist other subfolders named as&nbsp;Scene 's Collection 's Objects' States' Combination Y. Each of those folders contains images of the different poses from the set camera view, given a&nbsp;different combination&nbsp;of background, lighting, glove- and cloth-like materials, and hand's a priori scaling state.</p><p>!!!!! IMPORTANT NOTE !!!!!</p><p>After some testing, an error in the ground truth of the small set of images was found. Please use only the big set found in the zip. For further instructions and questions, please contact us at prod@iti.gr.</p>

opencc-by-4.0Oct 2022View details →
zenodo40/100

MOVING: a Multi-MOdal dataset of EEG signals and VIrtual Glove hand trackING

<p>A new Multi-modal dataset comprising neural EEG signals and kinematic data associated with three hand movements &mdash; open/close, finger tapping, and wrist rotation &mdash; along with a rest period. The dataset, obtained from eleven subjects using a 32-channel dry wireless EEG system, also includes synchronized kinematic data captured by a Virtual Glove (VG) system equipped with two orthogonal Leap Motion Controllers. The use of these two devices allows for fast assembly (~ 1 minute) while introducing more noise than the gold standard devices for data acquisition. The data set, obtained from 11 subjects using a 32-channel dry wireless EEG system, also includes synchronized kinematic data captured by a Virtual Glove (VG) system equipped with two orthogonal Leap Motion Controllers.&nbsp;</p> <p>For citation please refer to the paper:<br>Mattei, E.; Lozzi, D.; Di Matteo, A.; Cipriani, A.; Manes, C.;&nbsp;Placidi, G. MOVING: A Multi-Modal Dataset of EEG Signals and Virtual Glove Hand Tracking. Sensors 2024,24, 5207.&nbsp; https://doi.org/10.3390/s24165207&nbsp;</p> <p><strong>References</strong>:</p> <p>Placidi, Giuseppe. "<em>A smart virtual glove for the hand telerehabilitation.</em>" Computers in Biology and Medicine 37.8 (2007): 1100-1107.</p> <p>Placidi, Giuseppe, et al. "<em>Measurements by a LEAP-based virtual glove for the hand rehabilitation.</em>" Sensors 18.3 (2018): 834.</p> <p>Placidi, Giuseppe, et al. "<em>Patient&ndash;therapist cooperative hand telerehabilitation through a novel framework involving the virtual glove system.</em>" Sensors 23.7 (2023): 3463.</p>

opencc-by-4.0Jul 2024View details →
zenodo40/100

KGlove+Glove embedding for MAKG citation network

<p>Entity embedding by using KGlove+Glove on MAKG citation network (citation network from&nbsp;<a href="https://zenodo.org/record/4617285/files/08.PaperReferences.nt.bz2?download=1">https://zenodo.org/record/4617285/files/08.PaperReferences.nt.bz2?download=1</a>)</p>

opencc-by-4.0Mar 2022View details →
zenodo40/100

Problems Using Data Gloves with Strain Gauges to Measure Distal Interphalangeal Joints' Kinematics (Experimental data)

<p>Experimental data from <em>&quot;Problems Using Data Gloves with Strain Gauges to Measure Distal Interphalangeal Joints&rsquo; Kinematics&quot;,&nbsp;</em>available in Sensors.</p> <p>&nbsp;</p> <p><strong>&quot;PHASE I - STATIC POSTURES, FREE MOTION AND GRASPING TASKS.xlsx&quot;&nbsp;</strong>&nbsp;contains raw data of CyberGlove data glove of 22DoF while performing experiments detailed in Phase I.</p> <p>Jonts labelled as in&nbsp;<a href="https://www.nature.com/articles/s41597-019-0175-6">Human hand kinematic data during feeding and cooking tasks</a>.&nbsp;</p> <p>Task order detailed in &quot;PHASE I TASK ORDER.txt&quot;.</p> <p>Subjects&#39; hand length detailed in &quot;PHASE I SUBJECT DATA.txt&quot;.</p> <p>&nbsp;</p> <p><strong>&quot;PHASE II - SOLLERMAN HAND FUNCTION TEST.xlsx&quot;&nbsp;</strong>&nbsp;contains joint angles recorded using&nbsp;CyberGlove data glove of 22DoF while performing experiments detailed in Phase II.</p> <p>Jont angles and sign criteria considered as in&nbsp;<a href="https://www.nature.com/articles/s41597-019-0175-6">Human hand kinematic data during feeding and cooking tasks</a>.</p> <p>Subjects&#39; hand length and laterality detailed in &quot;PHASE II SUBJECT DATA.txt&quot;.</p> <p>&nbsp;</p> <p>For further information please contact authors (rodaa@uji.es).</p>

opencc-by-4.0May 2022View details →
zenodo40/100

GLOVE_train_test_set.hdf5

<div> <div> <div> <p>GLOVE_100 dataset contains one million pre-trained Global&nbsp;Vectors for Word Representation (GloVe) embeddings that capture semantic relationships between words.&nbsp;These 100-dimensional embedding vectors were pre-trained on the combined Wikipedia 2014 + Gigaword&nbsp;5th Edition corpora (6B tokens, 400K vocabulary) and cover a wide range of English words, enabling&nbsp;comprehensive assessments of approximate similarity search methods across diverse vocabulary and&nbsp;word relationships.</p> </div> </div> </div>

opencc-by-4.0Jul 2024View details →
zenodo40/100

Evaluating a Kinematic Data Glove with Pressure Sensors to Automatically Differentiate Free Motion from Product Manipulation (Experimental Data)

<p>Experimental data from&nbsp;<em>&quot;Evaluating a kinematic data glove with pressure sensors to automatically differentiate free motion from product manipulation&quot;,&nbsp;</em>available at Applied Sciences.</p> <p>&quot;DATA.zip&quot; contains raw data collected using VMG30 and CyberGlove data gloves, in txt format.&nbsp;</p> <p>For further information please see the details in the manuscript or contact the corresponding author Alba Roda-Sales&nbsp;(rodaa@uji.es).</p>

opencc-by-4.0Jul 2023View details →
zenodo36/100

Niilo Tammisalo's bandy glove, 1920's

The goalkeeper Tammisalo won caps in bandy, football and ice hockey. Source: Objaverse 1.0 / Sketchfab

opencc-byJun 2021View details →
zenodo36/100

Eino Kaakkolahti's Pesäpallo Glove

This left-handed glove was originally made for baseball by the U.S. manufacturer Spalding. The famous pesäpallo player Eino Kaakkolahti acquired it in the early 1950's. Sports equipment of all kind were in short supply in Finland after the war, and American baseball gloves were in great demand among pesäpallo players. Pesäpallo is a Finnish variant of baseball, invented by Lauri "Tahko" Pihkala in the early 1920's. The first rules were codified in 1922. Pitcher Eino Kaakkolahti (1929–2014) was the most prominent player in the 1950's. Source: Objaverse 1.0 / Sketchfab

opencc-byJun 2021View details →
zenodo36/100

Nintendo Power Glove NES (photogrammetry)

Special thanks to www.gameovervideogames.com scan by austinbeaulier.com Austin Beaulier 2019 check out more retro video game scans on my page thanks! Created in RealityCapture by Capturing Reality from 87 images in 00h:12m:40s. Source: Objaverse 1.0 / Sketchfab

opencc-byApr 2019View details →
zenodo36/100

Mastic Museum Gloves

<p>Image from PIOP museum</p>

opencc-by-4.0May 2022View details →
zenodo36/100

Bethel Digital Lockdown: A Glove by Zach Haala

This is a model of one my baseball gloves. It is a Wilson A2000 1786 Model, and has been very representational of my covid-19 experience. Over the laboring months of lockdown, I was left without a job for a while, and with not much else going on becuase of the outbreak, I was left with much time to spend at the baseball field. Being an athlete at the collegiate level, working on my game is nothing new, however, this glove is not exactly representational of me improving my play, but rather provides symbolism for the hours a day I spent at the field as an escape from the reality that was the pandemic. Source: Objaverse 1.0 / Sketchfab

opencc-bySep 2020View details →
zenodo36/100

Boxing Glove from 1952 Olympic Games

This boxing glove made by the Finnish manufacturer Karhu carries the signatures of all boxing gold medalists at the Helsinki Olympic Games of 1952. The finals of the Olympic boxing tournament took place in Töölö Exhibition Hall on 2 August, one day before the closing ceremony of the Games. American boxers won five gold medals out of ten. The rest of the winners came from five different European countries. Pentti Hämäläinen of Finland delighted the home crowd by winning gold in the bantamweight division. Names on the glove: Nathan "Nate" Brooks (USA), flyweight (51 kg) Pentti Hämäläinen (Finland), bantamweight (54 kg) Ján Zachara (Czechoslovakia), featherweight (57 kg) Aureliano Bolognesi (Italy), lightweight (60 kg) Charles Adkins (USA), light welterweight (63.5 kg) Zygmunt Chychła (Poland), welterweight (67 kg) László Papp (Hungary), light middleweight (71 kg) Floyd Patterson (USA), middleweight (75 kg) Norvel Lee (USA), heavy middleweight (81 kg) Edward Sanders (USA), heavyweight (over 81 kg) Source: Objaverse 1.0 / Sketchfab

opencc-byJun 2021View details →
zenodo36/100

2.4 million GLOVE word/phrase vectors SQLite database trained on PubMed abstracts

<p>This is a 2.4 million GLOVE word/phrase vectors SQLite database trained on PubMed 2021 abstracts that can be used as word/phrase embeddings in machine learning applications.</p>

opencc-by-4.0Oct 2024View details →
zenodo36/100

MAGOS Glove Two Fingers EggPlant Pick and Place

<div> <div>Welcome to the Two_fingers_EggPlant_PickAndPlace dataset, a unique data collection showcasing human pick-and-place actions using a Magos Glove for the delicate object (in this case a vegetable - Eggplant). This dataset is designed to facilitate research in robotics and machine learning, particularly in human-robot interaction and manipulation, and to show how human manipulation knowledge can be transferred to intelligent gripper solutions.</div> </div>

opencc-by-4.0Nov 2024View details →
zenodo36/100

FIGURE 4 in Like A Glove: Do The Dimensions Of Male Adanal Suckers And Tritonymphal Female Docking Papillae Correlate In The Proctophyllodidae (Astigmata: Analgoidea)?

FIGURE 4: Size distributions of Proctophyllodes troncatus adult females, adult males and nymphs with and without docking papillae. Body size was measured as the length of the idiosoma (µm) from the anterior margin of the prodorsum to the posterior region of the body excluding the terminal hyaline appendages in adult females and the opisthosomal lamellae in males. Nymphs were catego- rized as having docking papillae or lacking docking papillae. Adult females were significantly larger than adult males as indicated by an unpaired t-test (t38 = 22.6, P &lt;0.001). Similarly, nymphs with docking papillae were larger on average than were those without docking papillae (t194 = 20.6, P &lt;0.001).

opencc-by-nd-4.0Mar 2014View details →
zenodo36/100

FIGURE 3 in Like A Glove: Do The Dimensions Of Male Adanal Suckers And Tritonymphal Female Docking Papillae Correlate In The Proctophyllodidae (Astigmata: Analgoidea)?

FIGURE 3: Correlations in morphology between adult male and tritonymphal female Neodectes spp., Proctophyllodes spp., and Proterothrix spp. feather mites (Astigmata: Proctophyllodidae). Correlations are illustrated between widths (A-B) and lengths (C-D) of the male adanal suckers and the female docking papillae. R2 values indicate how well variation in one variable is predicted by that of the other variable.

opencc-by-nd-4.0Mar 2014View details →
zenodo36/100

FIGURE 2 in Like A Glove: Do The Dimensions Of Male Adanal Suckers And Tritonymphal Female Docking Papillae Correlate In The Proctophyllodidae (Astigmata: Analgoidea)?

FIGURE 2: Correlation between adult male and tritonymphal female body length (µm) in Neodectes spp., Proctophyllodes spp., and Proterothrix spp. (Astigmata: Proctophyllodidae). Length of the idiosoma was measured from the anterior margin of the prodorsum to the posterior region of the body excluding the opisthosomal lamellae in males. Body size was positively correlated between the sexes (rs = 0.66, n = 32, P &lt;0.01) whereby larger tritonymphal females were paired with larger conspecific males.

opencc-by-nd-4.0Mar 2014View details →
zenodo36/100

FIGURE 1 in Like A Glove: Do The Dimensions Of Male Adanal Suckers And Tritonymphal Female Docking Papillae Correlate In The Proctophyllodidae (Astigmata: Analgoidea)?

FIGURE 1: Length of the idiosoma in Proctophyllodes spp. in A. female tritonymphs, B. adult females and C. adult males. Measurements (dashed line) were taken from the margin of the prodorsum to the posterior margin of the body. In female tritonymphs we measured the lateral length (A), medial length (B), and width (C) of the docking papillae. In adult males (D; ventral), we measured the distal (D) and basal (E) widths of the adanal suckers as well as sucker depth (F). Line drawings are modeled after Proctophyllodes glandarinus for adults and from Proctophyllodes pari for tritonymphs (Atyeo and Braasch, 1996). Diagrams of the docking papillae and adanal suckers are drawn after scanning electron images published in Witali´nski et al. (1992).

opencc-by-nd-4.0Mar 2014View details →
zenodo36/100

Italian GloVe models

<p>Italian GloVe models trained from scratch&nbsp;on a dataset composed of:</p> <p>- <strong>wiki</strong>: a&nbsp;dump of Italian Wikipedia (as of December 15, 2022), comprising 25,548,651 sentences and 526,640,982 words (3.2 GB of raw text);<br> - <strong>webz</strong>: a&nbsp;dataset of Italian news (159,226 documents) from the webz.io platform, crawled in October 2015, containing 44,041,823 sentences and 44,544,385 words (244 MB);<br> - a dataset of 5,510 Italian news articles from the newspaper ModenaToday&nbsp;(<strong>MT</strong>) or 15,115 documents from the Italian version of Reuters (<strong>RCV2</strong>).</p> <p><strong>glv_wiki_wbz_mt_20_epochs.zip</strong>: GloVe model trained on the&nbsp;dataset consisting of wiki, webz, and MT for 20 epochs</p> <p><strong>glv_wiki_wbz_mt_50_epochs.zip</strong>: GloVe model trained on the&nbsp;dataset consisting of wiki, webz, and MT for 50 epochs</p> <p><strong>glv_wiki_wbz_reut_20_epochs.zip</strong>: GloVe model trained on the&nbsp;dataset consisting of wiki, webz, and RCV2 for 20 epochs</p> <p><strong>glv_wiki_wbz_reut_50_epochs.zip</strong>: GloVe model trained on the&nbsp;dataset consisting of wiki, webz, and RCV2 for 50 epochs</p>

opencc-by-4.0Oct 2023View details →

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neuroscienceopenDocumentation, web resources, and API references are available online.
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dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

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openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record