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  • Search Condition : Filter (MeSH = Deep Learning*)
Species Resource Title
Human and Animal Cells iPS-MEF-Ng-20D-17(APS0001) Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data.
C.elegans Fast deep neural correspondence for tracking and identifying neurons in C. elegans using semi-synthetic training.
Cord blood stem cells for research CD34+ Human induced pluripotent stem cell formation and morphology prediction during reprogramming with time-lapse bright-field microscopy images using deep learning methods.
Human and Animal Cells HeLa(RCB0007) Automated detection of patterned single-cells within hydrogel using deep learning.
Cord blood stem cells for research Prediction of Human Induced Pluripotent Stem Cell Formation Based on Deep Learning Analyses Using Time-lapse Brightfield Microscopy Images.
Human and Animal Cells HUDEP-2(RCB4557) Multiplexed high-throughput localized electroporation workflow with deep learning-based analysis for cell engineering.
Human and Animal Cells HeLa(RCB0007) 3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.
Morning Glory AK1 Effectiveness of Create ML in microscopy image classifications: a simple and inexpensive deep learning pipeline for non-data scientists.
Human and Animal Cells HL60(RCB0041) Comparative mapping of crawling-cell morphodynamics in deep learning-based feature space.
GBIF Plant specimens of Ishikawa Museum of Natural History , Plant Specimens of The Cattle Museum , Long-term fauna and flora records of the experimental forests of the Forest Research Station of Hokkaido University, Japan , Plant specimens of Toyota City Nature Sanctuary , Plant specimens of Otaru Museum , Plant specimens of Komatsu City Museum , The 6-7th National Survey on the Natural Environment: Vegetation Survey , Vascular Plant Specimens of Yamagata Prefectural Museum , Vascular plant specimens of Akita Prefectural Museum , Herbarium, University Archives and Collections, Fukushima University, Japan (FKSE) , ... Automated conservation assessment of the orchid family with deep learning.
General Microbes JCM2499 , JCM1465 , JCM20478 Modeling growth limits of Bacillus spp. spores by using deep-learning algorithm.