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A labeled dataset of hand-captured images of restaurant receipts
<p>Photographing fiscal receipts has become increasingly common with the rise of online storage and accounting services. However, capturing images in uncontrolled environments often leads to distortions that can compromise Optical Character Recognition (OCR) techniques, rendering the output text unreadable. To address this problem, we propose an open-source expert filtering approach based on low-level features to identify and discard low-quality invoice images, select high-quality images, and flag images that require preparation prior to being processed for OCR. The dataset used in this work is an extension of the <a href="https://expressexpense.com/blog/free-receipt-images-ocr-machine-learning-dataset/">Express Expense SRD dataset</a>, which consists of 200 hand-photographed images of restaurant receipts. The free version of the original dataset has no OCR task labels. Since this information is needed to calculate the accuracy of the OCR and to analyze the effects of the proposed approach, we created a new version of the existing dataset with manual annotations for the receipts and also for the four corners of the documents.</p> <p>More information can be found at the following link: <a href="https://github.com/MaVILab-UFV/Filtering-Preparation-for-OCR_SIBGRAPI-2024">https://github.com/MaVILab-UFV/Filtering-Preparation-for-OCR_SIBGRAPI-2024</a></p> <p>If you use this data, please cite our paper as follows </p> <p>Auad, Manoela; Alves, Sarah; Kakizaki, Gabriel; Reis, Julio C. S.; Silva, Michel. A Filtering and Image Preparation Approach to Enhance OCR for Fiscal Receipts. In 37th Conference on Graphics, Patterns and Images (SIBGRAPI), 2024.</p>
Dataset - Hand-inspired Flying Grasper
<p>Dataset for manuscripts "Hand-inspired Flying Grasper".</p> <p>The file 'data_bags.zip' contains the experimental data packages (rosbag format) for all the autonomous experiments in the paper, which are recorded in the ROS system under Linux. By running the provided MATLAB-based code, all the data curves in the paper can be reproduced.</p> <p> </p>
Preliminary report: Reduced hand sensory and motor function in persons living with heart failure.
Open the record for dataset details and reuse information.
Data supporting the findings of the study: "Neural correlates of self-other distinction in patients with schizophrenia spectrum disorders: The roles of agency and hand identity"
<p>Data supporting the findings of the study. Details are specified in the readme file.</p>
Corticoreticulospinal tract neurophysiology in an arm and hand muscle in healthy and stroke subjects: Data
<p>Supplemental data of the paper: Corticoreticulospinal tract neurophysiology in an arm and hand muscle in healthy and stroke subjects.</p> <p>This dataset contains the individual raw data for healthy (H) and stroke subjects.</p>
FIGURE 6 in New conditions and intraspecific variations in hand and foot muscles in Pristimantis bogotensis (Peters, 1863) (Amphibia:Anura: Strabomantidae)
FIGURE 6. Superficial plantar muscles of the right foot of P. bogotensis. Scale 1mm. Abbreviations: Abd. br. dor. V = M. abductor brevis dorsalis digiti V; Abd. br. dor. hal. = M. abductor brevis dorsalis hallucis; Abd. prp. IV = M. abductor proprius digiti IV; Ext. br. dor. hal. = M. extensor brevis dorsalis hallucis; Ext. br. med. II = M. extensor brevis medius digiti II; Ext. br. med. hal. = M. extensor brevis medius hallucis;; Ext. br. sup. II = M. extensor brevis superficialis digiti II; Ext. br. prf. hal. = M. extensor brevis profundus hallucis; Ext. br. prf. II = Mm. extensores breves profundi digiti II; Ext. br. prf. III = Mm. extensores breves profundi digiti III; Ext. br. prf. IV = Mm. extensores breves profundi digiti IV; Ext. br. prf. V = Mm. extensores breves profundi digiti V; T. ant. = M. tarsalis anticus; T. post. = M. tarsalis posticus.
FIGURE 3 in New conditions and intraspecific variations in hand and foot muscles in Pristimantis bogotensis (Peters, 1863) (Amphibia:Anura: Strabomantidae)
FIGURE 3. Dorsolateral view of the right hand of P. bogotensis showing the m. abductor ulnocarpalis. Scale 1mm. Abbreviations: Abd. br. V = M. abductor brevis digiti V; Abd. ulncarp. = M. abductor ulnocarpalis; Ext. br. sup. V = M. extensor brevis superficialis digiti V; Ext. carp. uln. = M. extensor carpi ulnaris; Ext. dig. com. long. = M. extensor digitorum communis longus; Ext. br. dist. V = M. extensor brevis distalis digiti V; Palm. br. = M. palmaris brevis;
FIGURE 1 in New conditions and intraspecific variations in hand and foot muscles in Pristimantis bogotensis (Peters, 1863) (Amphibia:Anura: Strabomantidae)
FIGURE 1. Musculature of the right forearm of P. bogotensis. 1a. Dorsal view, superficial layer.1b. Ventral view of deep layer. Scale 1mm. Abbreviations: Abd. br. V = M. abductor brevis digiti V; Abd. ulncarp. = M. abductor ulnocarpalis; Epicondcub. = M. epicondylocubitalis; Ext. br.med. IV = M. extensor brevis medius digiti IV; Ext. br. sup. III = M. extensor brevis superficialis digiti III; Ext. br. sup. IV = M. extensor brevis superficialis digiti IV; Ext. br. sup. V = M. extensor brevis superficialis digiti V; Ext. carp. uln. = M. extensor carpi ulnaris; Ext. dig. com. long. = M. extensor digitorum communis longus; Ext. carp. rad. = M. extensor carpi radialis; Fl. antbr. lat. sup. = M. flexor antibrachii lateralis superficialis.
FIGURE 5 in New conditions and intraspecific variations in hand and foot muscles in Pristimantis bogotensis (Peters, 1863) (Amphibia:Anura: Strabomantidae)
FIGURE 5. Deep dorsal muscles of the right foot of P. bogotensis. Scale 1mm. Abbreviations: Abd. br. dor. hal. = M. abductor brevis dorsalis hallucis; Abd. br. plan hal = M. abductor brevis plantaris hallucis; Abd. br. plan. V = M. abductor brevis plantaris digiti V; Abd. prehal. = M. abductor prehallucis; Ap. plant. = Aponeurosis plantaris; Ext. br. prf. II = Mm. extensores breves profundi digiti II; Fl. os. mett. II = M. flexor ossis metatarsi digiti II; Fl. os. mett. III = M. flexor ossis metatarsi digiti III; Lumbr. br. II = Intphal. III = M. interphalangealis digiti III; Intphal. V = M. interphalangealis digiti V; Intphal. dist. IV = M. interphalangealis distalis digiti IV; Intphal. prox. IV = M. interphalangealis proximalis digiti IV; M. lumbricalis brevis digiti II; Lumbr. br. III = M. lumbricalis brevis digiti III; Lumbr. br. IV = M. lumbricalis brevis digiti IV; Lumbr. br. V = M. lumbricalis brevis digiti V; Lumbr. br. hal. = Lumbricalis brevis hallucis; Lumbr. long. III = M. lumbricalis longus digiti III; Lumbr. long. IV = M. lumbricalis longus digiti IV; Lumbr. long. V = M. lumbricalis longus digiti V; Lumbr. longis. IV = M. lumbricalis longissimus digiti IV; Op. hal. = M. opponens hallucis; T. sup. hal. = Tendo superficialis hallucis; T. sup. prodig. II = Tendo superficialis pro digiti II; T. sup. prodig. III = Tendo superficialis pro digiti III; T. sup. prodig. IV = Tendo superficialis pro digiti IV; T. sup. prodig. V = Tendo superficialis pro digiti V; Tr. plant. dist. = M. transversus plantae distalis.
FIGURE 7 in New conditions and intraspecific variations in hand and foot muscles in Pristimantis bogotensis (Peters, 1863) (Amphibia:Anura: Strabomantidae)
FIGURE 7. Deep plantar muscles of the right foot of P. bogotensis. Toe muscles. The Mm. lumbricales breves, lumbricales longus, opponens hallucis, and contrahentis digiti II were removed. Scale 1mm. Abd. br. plan. V = M. abductor brevis plantaris digiti V; Contr. II = M. contrahentis digiti II; Ext. br. prf. III = Mm. extensores breves profundi digiti III; Fl. t. II = M. flexor teres digiti II; Fl. t. III = M. flexor teres digiti III; Fl. t. IV = M. flexor teres digiti IV; Fl. t. V = M. flexor teres digiti V; Ext. br. prf. IV = Mm. extensores breves profundi digiti IV; Fl. os. mett. II = M. flexor ossis metatarsi digiti II; Fl. os. mett. III = M. flexor ossis metatarsi digiti III; Fl. os. mett. IV = M. flexor ossis metatarsi digiti IV; Tr. mett. 1 = M. transversus metatarsus 1; Tr. mett. 2 = M. transversus metatarsus 2; Tr. mett. 3 = M. transversus metatarsus 3.
FIGURE 4 in New conditions and intraspecific variations in hand and foot muscles in Pristimantis bogotensis (Peters, 1863) (Amphibia:Anura: Strabomantidae)
FIGURE 4. Deep palmar muscles of the left hand of P. bogotensis. Scale 1mm. Abbreviations: Abd. pols. = M. abductor pollicis; Abd. sec. V = M. abductor secundus digiti V; Add. pols. = M. adductor pollicis; Add. prp. V = Add. prp. V; Fl. ind. sup. prp. = M. flexor indicis superficialis proprius; M. Fl. os. metc. IV = flexor ossis metacarpi digiti IV; Fl. t. IV = M. flexor teres digiti IV; Fl. t. ind. = M. flexor teres indicis; Intcarp. = M. intercarpalis; Lumbr. br. III = M. lumbricalis brevis digiti III; Lumbr. ind. br. = M. lumbricalis indicis brevis; Lumbr. brv. V = Mm. lumbricalis brevis digiti V; Op. ind. = M. opponens indicis; Op. V = M. opponens digiti V; T. sup. c. prf. III = Tendo sup & caput prof digiti III; Tr. metc. 1 = M. transversus metacarpi 1; Tr. metc. 2 = M. transversus metacarpi 2; Fl. os. metc. III = M. flexor ossis metacarpi digiti III
Intrafascicular peripheral nerve stimulation produces fine functional hand movements in primates - Data and sample code
<p>This repository contains the processed data shown in the figures of the paper "<em>Intrafascicular peripheral nerve stimulation produces fine functional hand movements in primates", </em><em>Science Translational Medicine. </em>It also contains sample code for reference as a guideline to reproduce the analysis performed in the paper. </p>
FIGURE 4. Bolitoglossa tamaense, holotype. A. Dorsum. B. Head, lateral view. C. Hand. D. Leg. E. Head, dorsal view. F in Two New Species of Salamanders, Genus Bolitoglossa (Amphibia: Plethodontidae), from the Eastern Colombian Andes
FIGURE 4. Bolitoglossa tamaense, holotype. A. Dorsum. B. Head, lateral view. C. Hand. D. Leg. E. Head, dorsal view. F. Head, ventral view.
Hand mask for the RSNA bone age dataset
<p>Masks for semantic segmentation of hands from scanned X-Rays in the RSNA Bone Age dataset (released for the <a href="https://www.rsna.org/education/ai-resources-and-training/ai-image-challenge/rsna-pediatric-bone-age-challenge-2017">RSNA Pediatric Bone Age Challenge</a> in 2017).</p> <p>The masks were obtained manually using thresholding and edge detection and all masks were quality checked and, if needed, corrected.</p> <p>Based on this two models (Tensormask and Efficient-UNet) were trained to obtain the masks on the full RSNA Bone Age dataset.</p> <p> </p> <p>If you use this dataset for your work, please cite the paper this dataset is part of:</p> <p>Rassmann, S., Keller, A., Skaf, K. <em>et al.</em> Deeplasia: deep learning for bone age assessment validated on skeletal dysplasias. <em>Pediatr Radiol</em> <strong>54</strong>, 82–95 (2024). https://doi.org/10.1007/s00247-023-05789-1 </p> <p> </p>
The ROMI platform: a helping hand to farming communities
<p><strong>The following video describes the ROMI platform and explains how the set of tools can be adapted to different farming contexts. Funded by EU Grant 773875.</strong></p> <p><em>Videos are available in:</em></p> <ul> <li>Hi-res (1080p Apple ProRes)</li> <li>Mid-res (1080p H265)</li> </ul> <p><strong>Video script:</strong></p> <p>(MINCHIN) ROMI is robotics for micro-farms. It consists of a platform of robotic tools that can be customised, adapted to local situations. So understanding that these tools can be used in different ways is absolutely crucial to the project.<br> <br> (HANAPPE) We try to work on a number of tools that are open hardware, like the cable bot like the rover like the plant imager these are bricks that can be reused in different contexts different types of farms and that gradually what we want to build upon.<br> <br> (MINCHIN) Over four years of development and testing we've developed a platform of tools that can work together and that really goes from the ground-based rover which has got an ability to move around a plant and move to a plant in a field. We have above that a cable system, a cable bot which can be strung in a greenhouse situation or along a polyculture farm such as this one. We are using drones to be able to have an overall vision of the landscape and changes within the environment finally there's a phenotyping robot which is able to scan in detail a plant in a laboratory to help biologists or plant development biologists understand and map growth. These come together in what we're calling the farmers dashboard which allows somebody in situ to understand what they're seeing understand and analyse things which they can't see, and also provide data and data sets back into a laboratory or a computational situation to try and track and understand a complexity in much more depth, than has ever been able to be done before.<br> <br> (BAORI) Agricultural equipment in general you're looking at a hundred thousand pounds hundred thousand euros you name your your kind of uh your range but you're not accessible to someone who's got a very small farm okay so you're looking at a lot of money um the rover at the moment costs approximately seven to eight thousand euros to build. Now as a piece of industrial equipment, agricultural equipment that's that's very very cheap. We do have a very simple web interface that you can run on your phone to connect to the robot to tell it; I want a hoe for the next 25 meters, I want to do weeding. We use a playstation controller actually for just driving the rover around the field and this is something that anybody can learn to use very very quickly. We're kind of targeting somebody with very minimal technical knowledge so although you can build this and if you're a maker you can change the code you can change it to do what you want. We kind of envisage a situation where actually people will just download a complete package put it onto an Arduino, put it onto the raspberry pi. In fact that will install everything and then you're ready to go.<br> <br> (HANAPPE) The rover we intend to be the sort of most practical device, we've specialised it for weeding which is something for which there is a demand today.<br> <br> (OKADA) Our enemies i would say are the weeds as you can see and in summer it's terrible.<br> <br> (MINCHIN) One of the crucial demonstrators of the ROMI project is the weeding tool. Farmers dealing with complexity of a number of crops spend at least twenty percent of their time weeding. When we are able to weed mechanically this means that we don't use herbicides. And so weeding mechanically affords us a more organic way of agriculture and in this way the the weeding tool developed by ROMI is a demonstrator of what could be done to support some of these farmers dealing with a labor-intensive complexity on their farm. but the software the programming and the drivers of that sort of computation don't stop at weeding and we are able to go beyond mechanically into a whole potential of solutions.<br> <br> (HANAPPE) We would like to get them, these tools, in the field as soon as possible so that we can work with farmers and have their feedback but at the same time try to build a community around it, multi-disciplinary of farmers, engineers, researchers to improve these tools, augment their possibilities and then we'll see how far we get.<br> <br> (BESNARD) the ROMI project is interested in getting important information from the plant architecture and from the plant growth process it's very important for a farmer to get this information just to detect very early on if possible any deviations from the normal curves, if you have a pathogen attack for example you just notice very early sign of stress in your plants, and that's generally the pathogen is not like everywhere so it's much easier to to counter attack especially like in organic farming when you know like a lot of chemicals to do it. And at the same time we are developing a tool a technology to get as much information as we can from plant architecture and this has an application towards farmers to just monitor the growth of their crops. But this can have also another application for basic scientists like me just to understand the basic process of our plant built its own architecture which is a basic question.</p>
FIGURE 3. Rohdea urotepala Hand.-Mazz. A. Habit. B. Flower, vertical view. C. Inflorescence. D. Flower, longitudinal section. E. Flower, showing the interior. F in Rohdea rotiformis (Asparagaceae), a new species from Northern Sichuan, China
FIGURE 3. Rohdea urotepala Hand.-Mazz. A. Habit. B. Flower, vertical view. C. Inflorescence. D. Flower, longitudinal section. E. Flower, showing the interior. F. Perianth tube in transection. G. Ovary, in transection. H. One confluent flower with 10 stamens, vertical view. I. The ovary of one confluent flower, in transection. J. The back of a flower. K. One confluent flower, showing the interior. Photos by Hui Zhe Feng.
UnFAIR dataset for hands-on FAIR data sharing course
<p>UnFAIR dataset for hands-on FAIR data sharing course</p>
Fig. 10 in Benzobicyclic ketones, cycloheptenone oxide derivatives, guaiane-type sesquiterpenes, and alkaloids isolated from Taraxacum mongolicum Hand.-Mazz.
Fig. 10. NO production inhibited by compounds 3 and 11 (A) and IL-6 mRNA levels altered by compounds 3 and 11 (B) after RAW 264.7 macrophages were induced by 100 ng/mL LPS (DMSO was the blank control). The data are presented as the means ± SD (n = 3). Comparisons were made between the DMSO and LPS groups (##p <0.01) and between the LPS and different compound groups (*p <0.05; **p <0.01).
Acheulean Hand Axe (515a1-2)
**Acheulean hand axe** Location: St. Acheul Amiens, France. Period: Lower Paleolithic (before 300,000 years ago). Material: flint. Dimensions: length, 142.7 mm; width, 71.0 mm; thickness, 39.3 mm. Notes: Catalog no. 515a1 (specimen 2). This specimen is part of a larger collection of artifacts that was acquired in 1929 by James Bell Bullitt during a tour of western Europe and later donated to the University of North Carolina. Specimen resides in the North Carolina Archaeological Collection, Research Laboratories of Archaeology, University of North Carolina at Chapel Hill. Model by Kathleen Brock. Source: Objaverse 1.0 / Sketchfab
Medieval hand_cart
Large prop for your Mediaval or Fantasy scenerios Source: Objaverse 1.0 / Sketchfab
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.