MAIA-A machine learning assisted image annotation method for environmental monitoring and exploration. [PDF]
PLoS ONE, 2018 Digital imaging has become one of the most important techniques in environmental monitoring and exploration. In the case of the marine environment, mobile platforms such as autonomous underwater vehicles (AUVs) are now equipped with high-resolution ...
Martin Zurowietz +4 more
doaj +3 more sources
KaIDA: a modular tool for assisting image annotation in deep learning [PDF]
Journal of Integrative Bioinformatics, 2022 Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed.
Schilling Marcel P. +3 more
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Automatic Image Annotation Based on Deep Learning Models: A Systematic Review and Future Challenges
IEEE Access, 2021 Recently, much attention has been given to image annotation due to the massive increase in image data volume. One of the image retrieval methods which guarantees the retrieval of images in the same way as texts are automatic image annotation (AIA ...
Myasar Mundher Adnan +5 more
doaj +2 more sources
Assessing Representation Learning and Clustering Algorithms for Computer-Assisted Image Annotation—Simulating and Benchmarking MorphoCluster [PDF]
Sensors, 2022 Image annotation is a time-consuming and costly task. Previously, we published MorphoCluster as a novel image annotation tool to address problems of conventional, classifier-based image annotation approaches: their limited efficiency, training set bias ...
Simon-Martin Schröder, Rainer Kiko
doaj +2 more sources
Visual attention mechanism and support vector machine based automatic image annotation. [PDF]
PLoS ONE, 2018 Automatic image annotation not only has the efficiency of text-based image retrieval but also achieves the accuracy of content-based image retrieval. Users of annotated images can locate images they want to search by providing keywords.
Zhangang Hao, Hongwei Ge, Long Wang
doaj +2 more sources
A New Framework to Reduce Doctor’s Workload for Medical Image Annotation
IEEE Access, 2019 Accurate annotation of the medical image is the crucial step for image artificial intelligence (AI) clinical application. However, annotating medical image will incur a lot of annotation efforts and expense due to its high complexity and needing ...
Yang Deng +10 more
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Diverse Image Annotation [PDF]
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 In this work we study the task of image annotation, of which the goal is to describe an image using a few tags. Instead of predicting the full list of tags, here we target for providing a short list of tags under a limited number (e.g., 3), to cover as much information as possible of the image. The tags in such a short list should be representative and
Baoyuan Wu +3 more
openaire +2 more sources
Multi-Modal Multi-Scale Deep Learning for Large-Scale Image Annotation [PDF]
IEEE Transactions on Image Processing, 2018 Image annotation aims to annotate a given image with a variable number of class labels corresponding to diverse visual concepts. In this paper, we address two main issues in large-scale image annotation: 1) how to learn a rich feature representation ...
Chang, Shih-Fu +4 more
core +2 more sources
Image annotation with Photocopain [PDF]
, 2006 Photo annotation is a resource-intensive task, yet is increasingly essential as image archives and personal photo collections grow in size. There is an inherent conflict in the process of describing and archiving personal experiences, because casual ...
Brewster, Christopher +10 more
core +2 more sources
Image annotation and curation in radiology: an overview for machine learning practitioners. [PDF]
Eur Radiol Exp“Garbage in, garbage out” summarises well the importance of high-quality data in machine learning and artificial intelligence. All data used to train and validate models should indeed be consistent, standardised, traceable, correctly annotated, and de ...
Galbusera F, Cina A.
europepmc +2 more sources