Results 51 to 60 of about 6,675,235 (374)
Applied Sciences, 2021 Large amounts of high-quality image data are the basis and premise of the high accuracy detection of objects in the field of convolutional neural networks (CNN).
Ji’an You +3 more
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Image Annotation with Adobe Photoshop [PDF]
Journal of Digital Imaging, 2002 The authors relate the basic steps used to annotate grayscale cross sectional images with keyboard characters, arrowheads, and arrows using Adobe Photoshop 6.0 and 7.0.
Ronald D, Caruso, Gregory C, Postel
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Automatic Image Annotation Based on Co-Training
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
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Automatic Bounding Box Annotation with Small Training Datasets for Industrial Manufacturing
Micromachines, 2023 In the past few years, object detection has attracted a lot of attention in the context of human–robot collaboration and Industry 5.0 due to enormous quality improvements in deep learning technologies.
Manuela Geiß +4 more
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Image annotation with semi-supervised clustering [PDF]
2009 24th International Symposium on Computer and Information Sciences, 2008 Methods developed for image annotation usually make use of region clustering algorithms. Visual codebooks are generated from the region clusters of low level features. These codebooks are then, matched with the words of the text document related to the image, in various ways.
Sayar, Ahmet, Vural, Fatos T. Yarman
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Non-Structured Materials Science Data Sharing Based on Semantic Annotation
Data Science Journal, 2009 The explosion of non-structured materials science data makes it urgent for materials researchers to resolve the problem of how to effectively share this information. Materials science image data is an important class of non-structured data.
Changjun Hu +4 more
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Sensors, 2020 Since most computer vision approaches are now driven by machine learning, the current bottleneck is the annotation of images. This time-consuming task is usually performed manually after the acquisition of images.
Salma Samiei +4 more
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A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data [PDF]
, 2015 Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to deal with multimodal data, such as in image annotation tasks.
Larochelle, Hugo +2 more
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Tagging Like Humans: Diverse and Distinct Image Annotation [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 In this work we propose a new automatic image annotation model, dubbed diverse and distinct image annotation (D2IA). The generative model D2IA is inspired by the ensemble of human annotations, which create semantically relevant, yet distinct and diverse ...
Baoyuan Wu +5 more
semanticscholar +1 more source
Modeling, Classifying and Annotating Weakly Annotated Images Using Bayesian Network [PDF]
2009 10th International Conference on Document Analysis and Recognition, 2009 We propose a probabilistic graphical model to represent weakly annotated images. This model is used to classify images and automatically extend existing annotations to new images by taking into account semantic relations between keywords. The proposed method has been evaluated in classification and automatic annotation of images.
Barrat, Sabine, Tabbone, Salvatore
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