“…The time and cost of annotating ground-truth images and network training are major challenges to utilizing machine learning to automate the mining of volume electron microscopy data. …”
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“…In this paper, we examine the evidence, both historical and modern, and ultimately conclude that, while the truth may never be fully known, all evidence appears to indicate that loss of consciousness appears to occur within seconds of decapitation. …”
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“…Moreover, unlike the standard reweighting, in which the ratio in bins of two histograms at truth level is performed, multidimensional and unbinned information can be used as inputs to the DNN. …”
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“…The model showed high performance for predicting and matching the ground truth lameness data with the outputs of the algorithm. …”
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“…In the manual validation datasets, the ground truth step count was 367.4±359.4 steps while the mean bias was −0.4 steps (LoA −75.2, 74.3) or 0.1 %. …”
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“…We then trained a predictive model based on random forest using this truth set of 45 LOF variants and 45 GOF variants randomly selected from a set of variants tested by in vitro methods. …”
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“…CONCLUSION: For our use case and annotators, AICL facilitates rapid large-scale curation of high-quality ground truth. The proposed quality control regime can be employed by other investigators prior to embarking on AICL for segmentation tasks in large datasets.…”
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“…The models, code, and ground truth Koos grades for a subset of publicly available images (n = 188) will be released upon publication.…”
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“…The Bland-Altman plot between manually labelled ground truth and automated segmentation results produced a concordance correlation coefficient of 0.989, 95% limits of agreement between 865.4 and −562.4, and the vessels pixel count’s Pearson coefficient of correlation was 0.981 (P<0.01). …”
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“…To evaluate the quality of the fused images generated via our method, we employ a comprehensive set of evaluation metrics, including Structural Similarity Index Measurement (SSIM), which assesses the structural similarity between two images; Peak Signal-to-Noise Ratio (PSNR), which measures how closely the generated image resembles the ground truth; Entropy (E), which assesses the amount of information preserved or lost during fusion; the Feature Similarity Indexing Method (FSIM), which assesses the structural and feature similarities between two images; and Edge-Based Similarity (EBS), which measures the similarity of edges between the fused and ground truth images. …”
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“…RESULTS: We found good correlation between the VIs obtained from UAS platforms and ground-truth measurements and observed high broad-sense heritability for VIs. …”
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“…These matrices are derived from Pfam seed MSAs using a novel algorithm and thus build upon expert ground truth data covering a large and diverse sequence space. …”
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“…In this work, we investigated crowdsourcing strategies to increase the number of ground truth annotations and improve the quality of the KB. …”
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“…A total of 2400 contours were compared to the most probable ground truth with a 95% confidence level (S95) in similarity, sensitivity, and specificity using the simultaneous truth and performance level estimation (STAPLE) algorithm. …”
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“…We present a novel method for ground-truth labelling of cardiac magnetic resonance imaging (CMR) image data by leveraging multiple clinician experts ranking multiple images on a single ordinal axis, rather than manual labelling of one image at a time. …”
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“…The OMERACT filter was applied and the three domains of validation assessed. Truth assessments included cognitive interviewing, sensitivity analysis and Spearman’s correlations. …”
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“…Dice similarity coefficient (DSC) and mean distance to agreement (MDA) with ground truth contours were calculated slice by slice to quantify the contour accuracy. …”
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“…Furthermore, we noticed that the unsupervised result was closer to the ground-truth cell labels, after removing the sensitive genes detected by our tools. …”
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“…We compared the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. …”
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“…To generate the ground-truth data or the training data for the machine learning models, we determine the N spectrum of the soil samples (collected from a farm) using LIBS and develop a calibration model using the correlation between actual TN of the soil samples and the maximum intensity of N spectrum. …”
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