FastSME dataset

FastSME dataset EPENDYMAL CELLS Postnatal day 1 Centrin2GFP transgenic mouse, Ependymal cell junctions stained with βCatenin; nascent centrioles with mouse IgG2b anti-Sas-6 Confocal Apotome2 (Zeiss) CCD 40x 1024X1024 X58 0.18x0.18 x0.28 DENDRITES 14 days cerebellar mixed culture, Purkinje cells immunolabeled with calbindin, granule cells with VGLUT1 Confocal Leica SP5 PMT 63x 255X700 X32 0.06x0.06 x0.19 MEMBRANE1 Ependymal cell junctions stained with rab- bit anti-ZO1 (Life Technologies) Confocal Leica SP8 Hybrid 40x 407X421 X19 0.18x0.18 x0.28 NEURON1 GFP labeled Purkinje cell in 8 days cerebellar mixed culture Widefield Leica DMiRBE CCD 10x 168X201 X8 0.06x0.06 x0.19 NEURON2 CaPB labeled Purkinje cell in 7 days cerebellar mixed culture Confocal Leica SP5 PMT 63x 1024X1024 X31 0.06x0.06 x0.19 TUBULIN Primary cycling ependymal progenitor in vitro immunostained for tyrosinated tubulin Widefield Apotome 2 (Zeiss) CCD 100x 556X610 X21 0.065x0.065 x0.23 CANCER CELL Study of colocalization of huntingtin phosphorylation at serine 421 (S421-P-HTT) with cellcell junction at MCF10 Healthy cells Confocal Leica SP5 Hybrid 63x 512X512 X34 0.12x0.12 x0.125 NUCLEI Centrin2GFP transgenic mouse at P45, Ependymal cell necleus stained with DAPI, junctions stained with rabbit anti-ZO1 (Life Technologies) Confocal Leica SP8 Hybrid 63x 370X335 X24 0.121x0.121 x0.21 7 5 SYNTHETIC TISSUE Cell junctions and centrioles on a complex synthetic manifold Confocal 400X400 X128 - 0

Coral reef dataset

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Coral reef dataset

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

DTU - Drone inspection images of wind turbine

This dataset set has temporal inspection images for the years of 2017 and 2018 of the same 'Nordtank' wind turbine at DTU wind facilities in Roskilde, Denmark.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV