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Deep Learning for Three Types of Keratitis Classification based on Confocal Microscopy Images

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10792-019-01134-4openalex-snapshot

Role of in vivo confocal microscopy in the diagnosis of infectious keratitis

inferredcites →https://doi.org/10.1016/j.cmpb.2019.105019openalex-snapshot

Automatic diagnosis of fungal keratitis using data augmentation and image fusion with deep convolutional neural network

inferredcites →https://doi.org/10.1076/ceyr.27.2.111.15949openalex-snapshot

Neural network approach to classify infective keratitis

inferredcites →https://doi.org/10.1097/icl.0b013e3181e3ef26openalex-snapshot

Surgical Outcomes in Cases of Contact Lens-Related Fusarium Keratitis

inferredcites →https://doi.org/10.1109/access.2018.2808941openalex-snapshot

Hyphae Detection in Fungal Keratitis Images With Adaptive Robust Binary Pattern

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2019.00065openalex-snapshot

Bag of Tricks for Image Classification with Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/smartcloud.2016.26openalex-snapshot

Automatic Detecting Cornea Fungi Based on Texture Analysis

inferredcites →https://doi.org/10.1109/tii.2019.2943898openalex-snapshot

Deep Residual Shrinkage Networks for Fault Diagnosis

inferredcites →https://doi.org/10.1117/1.600871openalex-snapshot

Book Review: Handbook of Biological Confocal Microscopy, Second Edition. Edited by J. B. Pawley

inferredcites →https://doi.org/10.7150/ijbs.35630openalex-snapshot

The PACAP-derived peptide MPAPO facilitates corneal wound healing by promoting corneal epithelial cell proliferation and trigeminal ganglion cell axon regeneration

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4119213openalex-extracted

An Interpretable Deep Learning Approach for Automatic Diagnosis of Fungal Keratitis and Acanthamoeba Keratitis Based on an Introduced Database of in Vivo Confocal Microscopic Images

inferred← citeshttps://doi.org/10.1038/s41598-023-35085-9openalex-snapshot

Interpretable deep learning for diagnosis of fungal and acanthamoeba keratitis using in vivo confocal microscopy images

inferred← citeshttps://doi.org/10.3390/diagnostics13162655openalex-snapshot

Diagnosis of Acanthamoeba Keratitis: Past, Present and Future

inferred← citeshttps://doi.org/10.3390/life13112117openalex-snapshot

Artificial Intelligence and Infectious Keratitis: Where Are We Now?

inferred← citeshttps://doi.org/10.48175/ijarsct-30025openalex-snapshot

BioEyeNet: An Optimized Deep Learning Framework for Classification & prediction of Keratitis and Uveitis

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