Results 41 to 50 of about 6,675,235 (374)

Utilising semantic technologies for intelligent indexing and retrieval of digital images [PDF]

open access: yes, 2013
The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-
A Smeulders   +13 more
core   +2 more sources

An Efficient and Effective Model Based on Mean Positive Examples for Social Image Annotation

open access: yesIEEE Access, 2020
Nowadays, with the rapid growth of imaging and social network, huge volumes of image data are produced and shared on social media. Social image annotation has been an important and challenging task in the fields of computer vision and machine learning ...
Haiyu Song   +6 more
doaj   +1 more source

Large-scale medical image annotation with crowd-powered algorithms. [PDF]

open access: yesJ Med Imaging (Bellingham), 2018
. Accurate segmentations in medical images are the foundations for various clinical applications. Advances in machine learning-based techniques show great potential for automatic image segmentation, but these techniques usually require a huge amount of ...
Heim E   +14 more
europepmc   +2 more sources

Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions [PDF]

open access: yes, 2014
Structured-output learning is a challenging problem; particularly so because of the difficulty in obtaining large datasets of fully labelled instances for training.
A. Delong   +10 more
core   +3 more sources

Annotating historical archives of images [PDF]

open access: yesProceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries, 2008
Recent programs like the Million Book Project and Google Print Library Project have archived several million books in digital format, and within a few years a significant fraction of world’s books will be online. While the majority of the data will naturally be text, there will also be tens of millions of pages of images. Many of these images will defy
Xiaoyue Wang   +3 more
openaire   +1 more source

Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation [PDF]

open access: yesACM Multimedia, 2018
We introduce Fluid Annotation, an intuitive human-machine collaboration interface for annotating the class label and outline of every object and background region in an image. Fluid annotation is based on three principles:(I) Strong Machine-Learning aid.
Mykhaylo Andriluka   +2 more
semanticscholar   +1 more source

Trigraph Regularized Collective Matrix Tri-Factorization Framework on Multiview Features for Multilabel Image Annotation

open access: yesIEEE Access, 2019
Due to the explosive growth of image data, image annotation has been one of the most popular research directions in computer vision. It has been widely used in image retrieval, image analysis and understanding. Because traditional manual image annotation
Junyi Zhang   +3 more
doaj   +1 more source

Analysis of Underwater Image Processing Methods for Annotation in Deep Learning Based Fish Detection

open access: yesIEEE Access, 2022
With the advent of deep-learning (DL) techniques, image annotation has become a fundamental part of the research process. In the case of underwater image annotation, the human in charge of the task is faced whith the inherent quality problems of this ...
Jose-Luis Lisani   +5 more
doaj   +1 more source

A framework for evaluating automatic image annotation algorithms [PDF]

open access: yes, 2010
Several Automatic Image Annotation (AIA) algorithms have been introduced recently, which have been found to outperform previous models. However, each one of them has been evaluated using either different descriptors, collections or parts of collections ...
A.W.M. Smeulders   +12 more
core   +2 more sources

Cross-Domain Web Image Annotation [PDF]

open access: yes2009 IEEE International Conference on Data Mining Workshops, 2009
In recent years, cross-domain learning algorithms have attracted much attention to solve labeled data insufficient problem. However, these cross-domain learning algorithms cannot be applied for subspace learning, which plays a key role in multimedia, e. g., web image annotation. This paper envisions the cross-domain discriminative subspace learning and
Tao, D, Si, S, Chan, KP
openaire   +2 more sources

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