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Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection2023 arXiv (Cornell University) preprint Computer Science Information Retrieval and Search Behavior Open access
Sophia Althammer, Guido Zuccon, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury
0citations -
Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders2021 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Human Pose and Action Recognition Open access
Matthew R Whiteway, Dan Biderman, Yoni Friedman, Mario Dipoppa, E. Kelly Buchanan, Anqi Wu, +11 more
9citations -
Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders2021 PLoS Computational Biology article Computer Science Human Pose and Action Recognition Open access
Matthew R Whiteway, Dan Biderman, Yoni Friedman, Mario Dipoppa, E. Kelly Buchanan, Anqi Wu, +11 more
34citations -
The covariance perceptron: A new paradigm for classification and processing of time series in recurrent neuronal networks2020 PLoS Computational Biology article Computer Science Neural Networks and Applications Open access
Matthieu Gilson, David Dahmen, Rubén Moreno‐Bote, Andrea Insabato, Moritz Helias
11citations -
Development and validation of a supervised deep learning algorithm for automated whole‐slide programmed death‐ligand 1 tumour proportion score assessment in non‐small cell lung cancer
Liesbeth M. Hondelink, Melek Hüyük, Pieter E. Postmus, Vincent T.H.B.M. Smit, Sami Blom, Jan H. von der Thüsen, +1 more
49citations -
Fully automatic cardiac four chamber and great vessel segmentation on CT pulmonary angiography using deep learning2022 Frontiers in Cardiovascular Medicine article Computer Science Medical Image Segmentation Techniques Open access
Michael J. Sharkey, Jonathan Christopher Taylor, Samer Alabed, Krit Dwivedi, Kavita Karunasaagarar, Christopher Johns, +10 more
39citations