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22 results for “material recognition”
MatSim Dataset and benchmark for one-shot visual materials and textures recognition
<p><strong>The MatSim Dataset and benchmark</strong></p> <p>Synthetic dataset and real images benchmark for visual similarity recognition of materials and textures.</p> <p>MatSim: a synthetic dataset, a benchmark, and a method for computer vision-based recognition of similarities and transitions between materials and textures focusing on identifying any material under any conditions using one or a few examples (one-shot learning).</p> <p>Based on the paper: <a href="https://arxiv.org/pdf/2212.00648.pdf">One-shot recognition of any material anywhere using contrastive learning with physics-based rendering</a></p> <p> </p> <p><strong>Benchmark_MATSIM.zip: </strong>contain the benchmark made of real-world images as described in the paper</p> <p><strong>Dataset Generation Scripts.zip: </strong>Contain the Blender (4.1) Python scripts used for generating the dataset<br><br><a href="https://zenodo.org/record/7390166/files/MatSim_object_train_split_1.zip?download=1"><strong>MatSim_object_train_split_1,2,3....zip:</strong> </a>Contain a subset of the synthetics dataset for images of CGI images materials on random objects as described in the paper.</p> <p><strong>MatSimTrainObjectsNearField_.zip </strong>Contain train sets with near fieldlight sources</p> <p><strong><a href="https://zenodo.org/record/7390166/files/MatSim_Vessels_Train_1.zip?download=1">MatSim_Vessels_Train_1,2,3....zip </a></strong><a href="https://zenodo.org/api/files/020f90b2-7c41-44ad-86e3-69257884a569/MatSim_object_train_split_1.zip"><strong>:</strong> </a>Contain a subset of the synthetics dataset for images of CGI images materials inside transparent containers as described in the paper.<br><br><strong>*Note: these are subsets of the dataset; the full dataset can be found at:</strong><br><a href="https://e1.pcloud.link/publink/show?code=kZIiSQZCYU5M4HOvnQykql9jxF4h0KiC5MX">https://e1.pcloud.link/publink/show?code=kZIiSQZCYU5M4HOvnQykql9jxF4h0KiC5MX</a></p> <p>or<br><a href="https://icedrive.net/s/A13FWzZ8V2aP9T4ufGQ1N3fBZxDF">https://icedrive.net/s/A13FWzZ8V2aP9T4ufGQ1N3fBZxDF</a></p> <p> </p>
Videos For: One-shot recognition of any material anywhere using contrastive learning with physics-based renderin
<p>Demonstration Video:</p> <p>Image Recognition of Materials States And Types From Single Example Identifying the state of the material in the main video by matching it to a few reference images (top). Each image contains a specific material state or type. The best match image is marked green. Based on the net for identifying similarity between any material state and type. The code for the net and the trained model used for this is available at: https://github.com/sagieppel/Contrastive-learning-for-one-shot-materials-and-textures-similarity-recognition-from-images Paper : One-shot recognition of any material anywhere using contrastive learning with physics-based rendering. https://arxiv.org/abs/2212.00648</p>
Supplementary material 1 from: Caterino MS, Tishechkin AK (2020) Recognition and revision of the Phelister blairi group (Histeridae, Histerinae, Exosternini). ZooKeys 1001: 1-154. https://doi.org/10.3897/zookeys.1001.58447
Table S1. Taxa selected for the phylogenetic reanalysis performed in this paper, along with what data partitions were available and included
Supplementary material 4 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
SRP RNA multiple sequence alignment : Explanation note: Multiple sequence alignment with the SRP RNA sequences of Dumesic et al. (2015; Stereum hirsutum, Heterobasidion irregulare, and Heterobasidion annosum) aligned to our newly generated ITS sequences of Russula and Lactarius.
Supplementary material 3 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
ITS/SRP RNA multiple sequence alignment : Explanation note: Multiple sequence alignment comprising the 63 public ITS1 sequences with SRP RNA found in them, the three newly generated sequences, and the SRP RNA sequences from Dumesic et al. (2015) (Stereum hirsutum, Heterobasidion irregulare, and Heterobasidion annosum).
Supplementary material 2 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
ITS multiple sequence alignment : Explanation note: A multiple sequence alignment in the NEXUS format (Maddison et al. 1997) comprising all 63 matching ITS sequences, plus the three newly generated ones (KU356730, KU356731, and KU356732). The alignment was produced in MAFFT without manual adjustment (Katoh and Standley 2013). The alignment is composed of partial nSSU (bases 1-34 in the alignment), the full ITS1 (bases 35-678), the full 5.8S (bases 679-838), the full ITS2 (bases 839-1395), and partial nLSU (bases 1396-end). The SRP RNA occupies position 203-474 in the alignment. The alignment is provided for overview purposes only; the two-order nature of the taxa (Boletales and Russulales) coupled with the high variability of the ITS region jointly mean that the alignment will not be suited for phylogenetic inference.
Supplementary material 1 from: Rosenblad MA, Martín MP, Tedersoo L, Ryberg M, Larsson E, Wurzbacher C, Abarenkov K, Nilsson RH (2016) Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota). MycoKeys 13: 21-33. https://doi.org/10.3897/mycokeys.13.8579
Output from cmsearch and primers used : Explanation note: A) The output from cmsearch showing all 63 relevant matches to the three ectomycorrhizal lineages. B) Detail of the primers used to re-amplify the specimens.
Supplementary material 1 from: Sakuragui CM, Calazans LSB, de Oliveira LL, de Morais EB, Benko-Iseppon AM, Vasconcelos S, Schrago CEG, Joseph Mayo SJ (2018) Recognition of the genus Thaumatophyllum Schott − formerly Philodendron subg. Meconostigma (Araceae) − based on molecular and morphological evidence. PhytoKeys 98: 51-71. https://doi.org/10.3897/phytokeys.98.25044
Taxon sampling, voucher information and GenBank : Explanation note: Taxon sampling, voucher information and GenBank accession numbers of Philodendron, Homalomena and outgroup species.
Blast Furnace Raw Material Granularity Recognition Model Based on Deep Learning and Multimodal Fusion of 3D Point Cloud
<p>Provide data code</p>
Supplementary material 3 from: Ossowska E, Guzow-Krzemińska B, Kolanowska M, Szczepańska K, Kukwa M (2019) Morphology and secondary chemistry in species recognition of Parmelia omphalodes group – evidence from molecular data with notes on the ecological niche modelling and genetic variability of photobionts. MycoKeys 61: 39-74. https://doi.org/10.3897/mycokeys.61.38175
: Data type: multimedia
Supplementary material 1 from: Ossowska E, Guzow-Krzemińska B, Kolanowska M, Szczepańska K, Kukwa M (2019) Morphology and secondary chemistry in species recognition of Parmelia omphalodes group – evidence from molecular data with notes on the ecological niche modelling and genetic variability of photobionts. MycoKeys 61: 39-74. https://doi.org/10.3897/mycokeys.61.38175
: Data type: occurrence
Supplementary material 2 from: Ossowska E, Guzow-Krzemińska B, Kolanowska M, Szczepańska K, Kukwa M (2019) Morphology and secondary chemistry in species recognition of Parmelia omphalodes group – evidence from molecular data with notes on the ecological niche modelling and genetic variability of photobionts. MycoKeys 61: 39-74. https://doi.org/10.3897/mycokeys.61.38175
: Data type: multimedia
Supplementary material 4 from: Ossowska E, Guzow-Krzemińska B, Kolanowska M, Szczepańska K, Kukwa M (2019) Morphology and secondary chemistry in species recognition of Parmelia omphalodes group – evidence from molecular data with notes on the ecological niche modelling and genetic variability of photobionts. MycoKeys 61: 39-74. https://doi.org/10.3897/mycokeys.61.38175
: Data type: multimedia
Supplementary material 2 from: Lavoué S, Zafirah Ghazali S, Amirul Firdaus Jamaluddin J, Azizah Mohd Nor S, Zain KMd (2020) Genetic evidence for the recognition of two allopatric species of Asian bronze featherback Notopterus (Teleostei, Osteoglossomorpha, Notopteridae). Zoosystematics and Evolution 96(2): 449-454. https://doi.org/10.3897/zse.96.51350
DNA Data matrice
Supplementary material 1 from: Lavoué S, Zafirah Ghazali S, Amirul Firdaus Jamaluddin J, Azizah Mohd Nor S, Zain KMd (2020) Genetic evidence for the recognition of two allopatric species of Asian bronze featherback Notopterus (Teleostei, Osteoglossomorpha, Notopteridae). Zoosystematics and Evolution 96(2): 449-454. https://doi.org/10.3897/zse.96.51350
Table S1
Supplementary material 2 from: Caterino MS, Tishechkin AK (2020) Recognition and revision of the Phelister blairi group (Histeridae, Histerinae, Exosternini). ZooKeys 1001: 1-154. https://doi.org/10.3897/zookeys.1001.58447
Morphological and molecular phylogenetic data (NEXUS) for analysis of Phelister blairi group
Supplementary material 1 from: Rudoy A, Zhu C-D, Ferrari RR, Zhang Y-Z (2022) Integrative taxonomy based on morphometric and molecular data supports recognition of the three cryptic species within the Encyrtus sasakii complex (Hymenoptera, Encyrtidae). Journal of Hymenoptera Research 90: 129-152. https://doi.org/10.3897/jhr.90.75807
Tables and figures
Supplementary material 5 from: Petrželová I, Sochor M (2019) How useful is the current species recognition concept for the determination of true morels? Insights from the Czech Republic. MycoKeys 52: 17-43. https://doi.org/10.3897/mycokeys.52.32335
: Data type: molecular data
Supplementary material 4 from: Petrželová I, Sochor M (2019) How useful is the current species recognition concept for the determination of true morels? Insights from the Czech Republic. MycoKeys 52: 17-43. https://doi.org/10.3897/mycokeys.52.32335
: Data type: measurement
Supplementary material 3 from: Petrželová I, Sochor M (2019) How useful is the current species recognition concept for the determination of true morels? Insights from the Czech Republic. MycoKeys 52: 17-43. https://doi.org/10.3897/mycokeys.52.32335
: Data type: phylogenetic data
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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)
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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.