Automatic image annotation for fluorescent cell nuclei segmentation. [PDF]
PLoS ONE, 2021 Dataset annotation is a time and labor-intensive task and an integral requirement for training and testing deep learning models. The segmentation of images in life science microscopy requires annotated image datasets for object detection tasks such as ...
Fabian Englbrecht +2 more
doaj +6 more sources
Evaluating the use of Instagram images color histograms and hashtags sets for automatic image annotation [PDF]
Frontiers in Big Data, 2023 Color similarity has been a key feature for content-based image retrieval by contemporary search engines, such as Google. In this study, we compare the visual content information of images, obtained through color histograms, with their corresponding ...
Stamatios Giannoulakis +2 more
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
Learning based automatic face annotation for arbitrary poses and expressions from frontal images only [PDF]
, 2009 Statistical approaches for building non-rigid deformable models, such as the active appearance model (AAM), have enjoyed great popularity in recent years, but typically require tedious manual annotation of training images. In this paper, a learning based
, +4 more
core +4 more sources
Annotation-efficient deep learning for automatic medical image segmentation [PDF]
Nature Communications, 2021 Existing high-performance deep learning methods typically rely on large training datasets with high-quality manual annotations, which are difficult to obtain in many clinical applications.
Shanshan Wang +14 more
doaj +2 more sources
Automatic Multilevel Medical Image Annotation and Retrieval [PDF]
Journal of Digital Imaging, 2007 Image retrieval at the semantic level mostly depends on image annotation or image classification. Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. To address first issue, multilevel features are extracted to construct
Ahmed Mueen +2 more
openalex +5 more sources
Automatic Image Annotation Based on Co-Training [PDF]
Journal of Algorithms & Computational Technology, 2014 Automatic image annotation is a critical and challenging problem in pattern recognition and image understanding areas. There are some problems in existing automatic image annotation areas.
Xiao Ke, Guolong Chen
doaj +2 more sources
Automatic Image Annotation by Sequentially Learning From Multi-Level Semantic Neighborhoods [PDF]
IEEE Access, 2021 Automatic image annotation is a key technology in image understanding and pattern recognition, and is becoming increasingly important in order to annotate large-scale images.
Houjie Li +5 more
doaj +2 more sources
Automatic image annotation method based on a convolutional neural network with threshold optimization. [PDF]
PLoS One, 2020 Cao J, Zhao A, Zhang Z.
europepmc +3 more sources
Tags Re-ranking Using Multi-level Features in Automatic Image Annotation [PDF]
Journal of Advances in Computer Engineering and Technology, 2019 Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among ...
Forogh Ahmadi, Vafa Maihami
doaj +1 more source