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  1. 4201
    “…Material decomposition error was evaluated as the distance in basis material space between the estimated thicknesses and ground truth. Results: There was no clear trend between count-rate level and material decomposition error for all test materials except neoprene. …”
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    Experimental study of photon-counting CT neural network material decomposition under conditions of pulse pileup
  2. 4202
    “…The experimental results show that our proposed method yields a better spreading performance of the seed spreaders over a large variety of network connectivity structures, and correlates well with ranking based on an SIR model used as ground truth. It also out-performs contemporary techniques and is competitive with more sophisticated approaches that are computationally cost.…”
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    Best influential spreaders identification using network global structural properties
  3. 4203
    “…The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a ground truth for foetal heart activity when an invasive scalp lead is unavailable. …”
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    A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research
  4. 4204
    “…Registration of histopathology images from patients who had radical prostatectomy to pre-operative MRI allows such mapping of ground truth cancer labels onto MRI. However, traditional MRI-histopathology registration approaches are computationally expensive and require careful choices of the cost function and registration hyperparameters. …”
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    ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate
  5. 4205
    “…The SAE approach allows for morphological ground truth data collection and assignment of individual axons to functional phenotypes with direct implications for fiber mapping and neuromodulation studies.…”
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    A shape-adjusted ellipse approach corrects for varied axonal dispersion angles and myelination in primate nerve roots
  6. 4206
    “…Resulted accuracy for AlexNet and GoogleNet when tested against the majority vote as ground truth was of 85.51% and 74.75%, respectively. This result was higher than the score obtained on the dataset that they were trained on, showing their generalization capabilities. …”
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    Agreement of two pre-trained deep-learning neural networks built with transfer learning with six pathologists on 6000 patches of prostate cancer from Gleason2019 Challenge
  7. 4207
    “…The combination of the three imaging modes allowed for high correlation between optical image analysis and histological ground-truth. The initial results are encouraging, showing instrument capability to assess margins on clinical specimens with a positive predictive value of 1.0 and a negative predictive value of 0.83.…”
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    Assessment of breast cancer surgical margins with multimodal optical microscopy: A feasibility clinical study
  8. 4208
    “…One aspect is the large amount of cases needed and another is the necessity of high-quality ground truth annotation. The aim of the project was to establish and describe the construction of a database with substantial amounts of detail-annotated oncology imaging data from pathology and radiology. …”
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    Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training
  9. 4209
    por Perevaryukha, A. Yu.
    Publicado 2021
    “…Systems of differential equations with the dynamically redefinable right-hand side at special moments (events) are used. The truth conditions for transitions are obtained from computing other equations for additional characteristics of the state of a generation. …”
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    Methodology of the Construction of Computational Scenarios for Modeling Extreme States in Living Systems
  10. 4210
    por Katahira, Kentaro, Toyama, Asako
    Publicado 2021
    “…Such a situation occurs when the ground-truth learning rate differs between groups but a common learning rate is used, as per previous studies. …”
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    Revisiting the importance of model fitting for model-based fMRI: It does matter in computational psychiatry
  11. 4211
    “…Here, we propose clustering by increasing the rand index via coordinate ascent (CIRCA): an unsupervised, data-driven clustering method for deriving ground-truth scene categories. In Experiment 1, human participants organized 80 stereoscopic images of outdoor scenes from the Southampton-York Natural Scenes (SYNS) dataset (Adams et al., 2016) into discrete categories. …”
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    Category systems for real-world scenes
  12. 4212
    por Magnano, Chris S., Gitter, Anthony
    Publicado 2021
    “…Due to the exploratory nature of pathway reconstruction, there is no ground truth for direct evaluation, so parameter tuning methods typically used in statistics and machine learning are inapplicable. …”
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    Automating parameter selection to avoid implausible biological pathway models
  13. 4213
    por Yi, Faliu, Park, Seonghwan, Moon, Inkyu
    Publicado 2021
    “…Approach: The raw diffraction patterns of RBCs were recorded by use of DHM. Ground-truth mask images were labeled based on phase images reconstructed from RBC holograms using numerical reconstruction algorithm. …”
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    High-throughput label-free cell detection and counting from diffraction patterns with deep fully convolutional neural networks
  14. 4214
    “…Mainstream methods treat head pose estimation as a supervised classification/regression problem, whose performance heavily depends on the accuracy of ground-truth labels of training data. However, it is rather difficult to obtain accurate head pose labels in practice, due to the lack of effective equipment and reasonable approaches for head pose labeling. …”
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    Head Pose Estimation through Keypoints Matching between Reconstructed 3D Face Model and 2D Image
  15. 4215
    “…“Process of discovery” was the second overarching theme marking the journey of participants in finding the exact truth about diabetes and learning the consequences of ignoring their responsibility in diabetes care. …”
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    Understanding the Turning Point of Patients with Diabetes
  16. 4216
    “…We demonstrate that PolySTest with integrated Miss test achieves higher confidence and higher sensitivity for artificial and experimental proteomics data sets with known ground truth. Application of PolySTest to mass spectrometry based large-scale proteomics data obtained from differentiating muscle cells resulted in the rescue of 10–20% additional proteins in the identified molecular networks relevant to muscle differentiation. …”
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    PolySTest: Robust Statistical Testing of Proteomics Data with Missing Values Improves Detection of Biologically Relevant Features
  17. 4217
    por Shen, Yao, Yan, Zhipeng
    Publicado 2021
    “…More than 50% of the models built with the same data set or with independent data sets successfully predicted the testing set with significant correlation to the ground truth data. Features selected by our models were also significantly enriched in known drug transporters annotated in DrugBank for more than 60% of the models. …”
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    Systematic prediction of drug resistance caused by transporter genes in cancer cells
  18. 4218
    “…We conducted field experiments and proximal sensing campaigns to acquire the ground truth data and RAS images of wheat growth conditions and yields. …”
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    Simulation of Wheat Productivity Using a Model Integrated With Proximal and Remotely Controlled Aerial Sensing Information
  19. 4219
    “…All the predicted radiographic parameters were significantly correlated with ground truth values (all p < 0.001). The human and artificial intelligence comparison revealed that the deep learning model was capable of matching the reliability of doctors for 15/18 of the parameters. …”
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    Deep learning approach for automatic landmark detection and alignment analysis in whole-spine lateral radiographs
  20. 4220
    “…We designed a “crappifier” that computationally degrades high SNR, high pixel resolution ground truth images to simulate low SNR, low-resolution counterparts for training PSSR models that can restore real-world undersampled images. …”
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    Deep Learning-Based Point-Scanning Super-Resolution Imaging
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