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24 results for “Character recognition”
Figure 6 in Adulthood and phylogenetic analysis in gastropods: character recognition and coding in shells of Lavigeria (Cerithioidea, Thiaridae) from Lake Tanganyika
Figure 6. Plots of length against PC1 for all eight species of Lavigeria studied with regressed lines and R2 values. Length values are log transformed.
Figure 3 in Adulthood and phylogenetic analysis in gastropods: character recognition and coding in shells of Lavigeria (Cerithioidea, Thiaridae) from Lake Tanganyika
Figure 3. Character state APPL. An adult specimen of L. n. sp. X (left) and a juvenile (right). Notice the perimetric, wrinkle-like, lines on the front surface of the apertural lip of the adult. Scale bar = 0.2 cm.
Figure 7 in Adulthood and phylogenetic analysis in gastropods: character recognition and coding in shells of Lavigeria (Cerithioidea, Thiaridae) from Lake Tanganyika
Figure 7. Fifty per cent majority-rule consensus trees of five, nine, ten and 31 trees (from top to bottom, respectively) from four matrices. Matrices are coding the data of Table 1. See Analysis for explanation of the matrices. Tree and character statistics are given in Table 3. Optimality criterion: maximum parsimony, exhaustive search. All characters binary, of equal weight and unordered. Numbers indicate percentage of topologies that include the respective branches.
Figure 5 in Adulthood and phylogenetic analysis in gastropods: character recognition and coding in shells of Lavigeria (Cerithioidea, Thiaridae) from Lake Tanganyika
Figure 5. Character states DFST, AXRB and UEPW. Adult specimens of (A) L. n. sp. W, (B) L. n. sp. F, (C) L. n. sp. K, (D) L. n. sp. J showing the aperture in side view and (E) an apertural view of an adult L. n. sp. W. In A-D the trajectory of the suture tends to deviate downwards in comparison to the trajectory of the spiral cord of the previous whorl immediately above the suture (DFST). A and D also show the loss of, or irregularities in the appearance of axial sculpture (AXRB). In E, arrowheads show the undulations formed at the edge of the parietal side of the aperture (UEPW). Scale bar = 0.2 cm.
Figure 2 in Adulthood and phylogenetic analysis in gastropods: character recognition and coding in shells of Lavigeria (Cerithioidea, Thiaridae) from Lake Tanganyika
Figure 2. Character states WGPW and APLT. An adult specimen of L. n. sp. A (left) and a juvenile (right). The adult shows a thickened (APLT) and opaque (WGPW) inner surface of the apertural lip in comparison to the juvenile. Scale bar = 0.2 cm.
Figure 1 in Adulthood and phylogenetic analysis in gastropods: character recognition and coding in shells of Lavigeria (Cerithioidea, Thiaridae) from Lake Tanganyika
Figure 1. Eight species used in this study, apertural and side views of adult specimens. (A) Lavigeria new species N. (B) L. n. sp. F. (C) L. n. sp. J. (D) L. n. sp. X. (E) L. n. sp. K. (F) L. n. sp. W. (G) L. n. sp. A. (H) L. n. sp. U. C-H all belong to the same clade. A and B belong to different clades within the genus. Scale bar = 0.2 cm.
Figure 4 in Adulthood and phylogenetic analysis in gastropods: character recognition and coding in shells of Lavigeria (Cerithioidea, Thiaridae) from Lake Tanganyika
Figure 4. Character state APDT. An adult specimen of L. n. sp. J (left) and a juvenile on the right. Notice in the adult how the parietal side of the apertural lip is completely detached from the previous whorl and a false umbilicus has developed. Scale bar = 0.2 cm.
Data from: Hybridization, reinforcement selection and sex-dependent reproductive character displacement of sperm and egg recognition proteins
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Low resolution scanned text dataset for optical character recognition
<p>A collection of scanned pages of English text designed for testing low resolution OCR systems. There are 11 different pieces of text, each of which contains 5 pages of text. Each of these 55 pages is typeset in 18 different fonts and then scanned at 300 dpi, producing a total of 990 pages of scanned text. Downsampled 60 dpi and 75 dpi versions are included.</p>
Data from: Divergence in female damselfly sensory structures is consistent with a species recognition function but shows no evidence of reproductive character displacement
Males and females transmit and receive signals prior to mating that convey information such as sex, species identity, or individual condition. In some animals, tactile signals relayed during physical contact between males and females before and during mating appear to be important for mate choice or reproductive isolation. This is common among odonates, when a male grasps a female's thorax with his terminal appendages prior to copulation, and the female subsequently controls whether copulation occurs by bending her abdomen to complete intromission. It has been hypothesized that mechanosensory sensilla on the female thoracic plates mediate mating decisions, but is has been difficult to test this idea. Here, we use North American damselflies in the genus Enallagma (Odonata: Coenagrionidae) to test the hypothesis that variation in female sensilla traits is important for species recognition. Enallagma anna and E. carunculatum hybridize in nature, but experience strong reproductive isolation as a consequence of divergence in male terminal appendage morphology. We quantified several mechanosensory sensilla phenotypes on the female thorax among multiple populations of both species and compared divergence in these traits in sympatry versus allopatry. Although these species differed in features of sensilla distribution within the thoracic plates, we found no strong evidence of reproductive character displacement among the sensilla traits we measured in regions of sympatry. Our results suggest that species‐specific placement of female mechanoreceptors may be sufficient for species recognition, although other female sensory phenotypes might have diverged in sympatry to reduce interspecific hybridization.
A benchmark dataset for Manipuri Meetei-Mayek handwritten character recognition
<p>A benchmark dataset is always required for any classification or recognition system. To the best of our knowledge, no benchmark dataset exists for handwritten character recognition of Manipuri Meetei-Mayek script in <strong>public domain</strong> so far. Manipuri, also referred to as Meeteilon or sometimes Meiteilon, is a Sino-Tibetan language and also one of the Eight Scheduled languages of Indian Constitution. It is the official language and lingua franca of the southeastern Himalayan state of Manipur, in northeastern India. This language is also used by a significant number of people as their communicating language over the north-east India, and some parts of Bangladesh and Myanmar. It is the most widely spoken language in Northeast India after Bengali and Assamese languages. In this work, we introduce a handwritten Manipuri Meetei-Mayek character dataset which consists of more than 5000 data samples which were collected from a diverse population group that belongs to different age groups (from 4 years to 60 years), genders, educational backgrounds, occupations, communities from three different districts of Manipur, India (Imphal East District, Thoubal District and Kangpokpi District) during March and April 2019. Each individual was asked to write down all the Manipuri characters on one A4-size paper. The recorded responses are scanned with the help of a scanner and then each character is manually segmented from the scanned images. This dataset consists of segmented scanned images of handwritten Manipuri Meetei-Mayek characters (Mapi Mayek, Lonsum Mayek, Cheitap Mayek, Cheising Mayek, Khutam Mayek) of size 128X128 pixels in .JPG format as well as in .MAT format.</p>
A Benchmark Dataset for Manipuri Meetei-Mayek Handwritten Character Recognition
<p>A benchmark dataset is always required for any classification or recognition system. To the best of our knowledge, no benchmark dataset exists for handwritten character recognition of Manipuri Meetei-Mayek script in <em><strong>public domain</strong></em> so far. Manipuri, also referred to as Meeteilon or sometimes Meiteilon, is a Sino-Tibetan language and also one of the Eight Scheduled languages of Indian Constitution. It is the official language and lingua franca of the southeastern Himalayan state of Manipur, in northeastern India. This language is also used by a significant number of people as their communicating language over the north-east India, and some parts of Bangladesh and Myanmar. It is the most widely spoken language in Northeast India after Bengali and Assamese languages. In this work, we introduce a handwritten Manipuri Meetei-Mayek character dataset which consists of more than 5000 data samples which were collected from a diverse population group that belongs to different age groups (from 4 years to 60 years), genders, educational backgrounds, occupations, communities from three different districts of Manipur, India (Imphal East District, Thoubal District and Kangpokpi District) during March and April 2019. Each individual was asked to write down all the Manipuri characters on one A4-size paper. The recorded responses are scanned with the help of a scanner and then each character is manually segmented from the scanned images. This dataset consists of segmented scanned images of handwritten Manipuri Meetei-Mayek characters (Mapi Mayek, Lonsum Mayek, Cheitap Mayek, Cheising Mayek, Khutam Mayek) of size 128X128 pixels in .JPG format as well as in .MAT format.</p>
FIGURE 2. Morphological characters mapped onto a 95 in Revised circumscription of Nothofagus and recognition of the segregate genera Fuscospora, Lophozonia, and Trisyngyne (Nothofagaceae)
FIGURE 2. Morphological characters mapped onto a 95% bootstrap consensus tree, derived from Sauquet et al. (2012) (Analysis 2) for Fuscospora (Nothofagus subgenus Fuscospora), Lophozonia (Nothofagus subgenus Lophozonia), Nothofagus (Nothofagus subgenus Nothofagus), and Trisyngyne (Nothofagus subgenus Brassospora).
A benchmark dataset for Manipuri Meetei-Mayek handwritten character recognition
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Data from: Divergence in female damselfly sensory structures is consistent with a species recognition function but shows no evidence of reproductive character displacement
Open the record for dataset details and reuse information.
Trained tesseract networks for low-resolution optical character recognition
<p>Tesseract eng.traineddata files for low-resolution optical character recognition (English).</p>
Table 1. Morphological diagnostic characters delimiting H in Morphological and environmental variation within Hibiscus krichauffianus (Malvaceae), and the recognition of two new species, H. verecundus and H. calcareus
<p>Table 1. Morphological diagnostic characters delimiting <i>H. krichauffianus</i> sens. strict., and the three new entities.</p><table><tbody><tr><th>Character</th><th>Morphotype A – <i>Hibiscus krichauffianus</i></th><th>Morphotype B – <i>Hibiscus verecundus</i></th><th>Morphotype C – <i>Hibiscus calcareus</i></th><th>Morphotype D – <i>Hibiscus</i> sp. Belele (D.W.Goodall 3417)</th></tr></tbody><tbody><tr><th>Substrate preference</th><td>Deep sand</td><td>Typically shallow soils over sandstone, laterite or basalt</td><td>Lime-rich soils</td><td>Insufficient data</td></tr><tr><th>Plant habit</th><td>Subshrub or shrub to ~1 m high, usually erect or ascending</td><td>Low spreading subshrub or shrub to ~0.5 m high, usually decumbent</td><td>Low subshrub to ~0.5 m high, spreading, dome-shaped or rounded</td><td>Low or dwarf subshrub or shrub to ~0.3 m high</td></tr><tr><th>Branchlet indumentum colour</th><td>Silvery-white, white, sometimes fading to yellowish-white</td><td>Yellowish-brown, sometimes fading to white</td><td>White, or silvery-white</td><td>White on younger branchlets, older branchlets becoming ferruginous (ferruginous rays and white rays sometimes on the same hair)</td></tr><tr><th>Stipule width (mm)</th><td>0.16–0.4</td><td>0.1–0.17</td><td>0.2–0.5</td><td>0.2–0.35</td></tr><tr><th>Leaf lamina colour (adaxial)</th><td>Whitish-silver to grey, becoming greyish-green with age</td><td>Green to dark green</td><td>Grey to silvery-white</td><td>Silvery–ferruginous</td></tr><tr><th>Leaf lamina shape</th><td>Mostly ovate to lanceolate or oblong, occasionally broadly ovate</td><td>Ovate to broadly ovate, rarely elliptic–ovate</td><td>Ovate, elliptic–ovate or oblong–ovate</td><td>Ovate to elliptic–ovate</td></tr><tr><th>Leaf lamina in transverse</th><td>Flat to weakly concave or weakly folded</td><td>Flat to weakly concave or weakly folded</td><td>Mostly strongly concave to vshaped (and appearing folded on many herbarium specimens)</td><td>Flat to weakly folded</td></tr><tr><th>Leaf lamina length and width (mm)</th><td>10–55 × 5–35</td><td>9–52 × 8–33</td><td>6–28 × 4–16</td><td>17–43 × 6–22</td></tr><tr><th>Leaf lamina base</th><td>Obtuse, truncate or very broadly cuneate</td><td>Broadly cuneate, obtuse or truncate</td><td>Broadly cuneate or truncate</td><td>Truncate, very slightly cordate or broadly obtuse</td></tr><tr><th>Leaf lamina margin</th><td>Crenate to dentate</td><td>Serrate to dentate, rarely crenate</td><td>Serrate to dentate or crenate, undulate, sinus between teeth up to halfway to midvein</td><td>Dentate to crenate</td></tr><tr><th>Abcision line (at peduncle–pedicel junction), whether visible and position</th><td>Not obvious, obscured by hairs, usually 1–2 mm from the base, rarely up to one-half length from the base</td><td>Sometimes obvious, one-third to one-half length from the base</td><td>±Obvious, sometimes obscured by hairs, usually in upper half, 2–17 (–24) mm from the base</td><td>±Obvious, sometimes obscured by hairs, approximately one-third length from the base</td></tr><tr><th>Number of epicalyx lobes</th><td>5–8 (rarely 10, rarely bifurcating)</td><td>5–7</td><td>7–8</td><td>5–6</td></tr><tr><th>Epicalyx length (Including fused portion, excluding receptacle) (mm)</th><td>7–16</td><td>6–10</td><td>4–14</td><td>6–12</td></tr><tr><th>Fusion of epicalyx lobes at base</th><td>Fused for 1–4 mm</td><td>Free or fused to 0.5 mm</td><td>Fused for 1–3.5 mm</td><td>Free or fused for up to 1 mm</td></tr><tr><th>Epicalyx lobes degree of curvature</th><td>Straight in flower, becoming recurved or rarely incurved in fruit</td><td>Straight</td><td>Straight in flower, becoming recurved in fruit</td><td>Straight in flower, becoming recurved in fruit</td></tr><tr><th>Corolla colour</th><td>Pale pink or mauve (rarely white)</td><td>Pale pink or white (sometimes drying pale yellow)</td><td>Pale pink to mauve, sometimes almost white</td><td>Purple</td></tr><tr><th>Petal length (mm)</th><td>17–35</td><td>15–28</td><td>20–44</td><td>39–42</td></tr><tr><th>Seed indumentum</th><td>Patchy indumentum of wispy spreading, white to off-white hairs</td><td>Short patchy indumentum of appressed white to yellowish-brown hairs</td><td>Short patchy indumentum of appressed white hairs</td><td>Short patchy indumentum of appressed white to yellowish hairs</td></tr><tr><th>Seed length (mm, greatest dimension)</th><td>2–3</td><td>1.7–2.3</td><td>2.5–3</td><td>~3</td></tr><tr><th>Seed characteristic features or notes</th><td>Reniform (rarely subangular–reniform), funicular remnants brown, membranous and wing-like, on either side of the hilum</td><td>Two straighter sides almost forming a right angle at intersection, funicular remnants brown, membranous and wing-like, one centrally placed and one on either side of the hilum</td><td>Two straighter sides almost forming a right angle at intersection, funicular remnants brown, membranous and wing-like, on either side of the hilum</td><td>Two straighter sides almost forming a right angle at intersection, funicular remnants brown, membranous and wing-like, on either side of the hilum</td></tr><tr><th>Flower cleistogamy</th><td>Observed in some specimens</td><td>No evidence</td><td>Observed in a single specimen</td><td>Not observed in material examined</td></tr></tbody></table>
Figure 2 from: Drinkwater R, Cubey R, Haston E (2014) The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels. PhytoKeys 38: 15-30. https://doi.org/10.3897/phytokeys.38.7168
Figure 2 - Box plot of Complete and Partial Protocol results. R1C – Random 1 complete; R1P – Random 1 Partial; CollC – Collector only Complete; CollP – Collector only Partial; CouC – Country only Complete; CouP – Country only Partial; CCC – Collector & Country Complete; CCP – Collector & Country Partial; OCRC – Collector & Country OCR Complete; OCRP – Collector & Country OCR Partial; R2C – Random 2 Complete; R2P – Random 2 Partial.
Figure 1 from: Drinkwater R, Cubey R, Haston E (2014) The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels. PhytoKeys 38: 15-30. https://doi.org/10.3897/phytokeys.38.7168
Figure 1 - Example labels: a Pre-printed label with handwritten details b and c mixed labels with pre-printed and typed information d Mainly handwritten label, with printers mark e Mainly handwritten label with unusual phrasing.
Figure 4 from: Drinkwater R, Cubey R, Haston E (2014) The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels. PhytoKeys 38: 15-30. https://doi.org/10.3897/phytokeys.38.7168
Figure 4 - Digitiser responses to questions 1, 2 and 3 of survey
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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.