Results 51 to 60 of about 107,245 (331)

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

open access: yesMolecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh   +12 more
wiley   +1 more source

Relating visual and semantic image descriptors [PDF]

open access: yes, 2004
This paper addresses the automatic analysis of visual content and extraction of metadata beyond pure visual descriptors. Two approaches are described: Automatic Image Annotation (AIA) and Confidence Clustering (CC). AIA attempts to automatically classify
Cooke, Eddie   +4 more
core  

Automatic Annotation and Retrieval of Images [PDF]

open access: yesWorld Wide Web, 2002
Although a variety of techniques have been developed for content-based image retrieval (CBIR), automatic image retrieval by semantics still remains a challenging problem. We propose a novel approach for semantics-based image annotation and retrieval. Our approach is based on the monotonic tree model.
Song, Yuqing, Wang, Wei, Zhang, Aidong
openaire   +3 more sources

CD47 promotes mitogen‐activated protein kinase and epithelial‐to‐mesenchymal transition molecular programs to drive prometastatic phenotypes in non‐small cell lung cancer

open access: yesMolecular Oncology, EarlyView.
Beyond its role in immune evasion, this study identified that CD47 drives tumor‐intrinsic signaling in non‐small cell lung cancer (NSCLC). Transcriptomic profiling and functional studies revealed that CD47 regulates cell adhesion, migration, and metastasis through an ERK–EMT signaling axis.
Asa P.Y. Lau   +8 more
wiley   +1 more source

Bimodal network architectures for automatic generation of image annotation from text

open access: yes, 2018
Medical image analysis practitioners have embraced big data methodologies. This has created a need for large annotated datasets. The source of big data is typically large image collections and clinical reports recorded for these images.
Guo, Yufan   +4 more
core   +1 more source

A Data-Driven Approach for Tag Refinement and Localization in Web Videos [PDF]

open access: yes, 2015
Tagging of visual content is becoming more and more widespread as web-based services and social networks have popularized tagging functionalities among their users. These user-generated tags are used to ease browsing and exploration of media collections,
Ballan, Lamberto   +3 more
core   +4 more sources

Automatic Image Annotation for Semantic Image Retrieval

open access: yes, 2007
This paper addresses the challenge of automatic annotation of images for semantic image retrieval. In this research, we aim to identify visual features that are suitable for semantic annotation tasks. We propose an image classification system that combines MPEG-7 visual descriptors and support vector machines.
Shao, Wenbin, Naghdy, G., Phung, Son Lam
openaire   +3 more sources

Mycobacterial cell division arrest and smooth‐to‐rough envelope transition using CRISPRi‐mediated genetic repression systems

open access: yesFEBS Open Bio, EarlyView.
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point   +7 more
wiley   +1 more source

Automatically Annotating the MIR Flickr Dataset: Experimental Protocols, Openly Available Data and Semantic Spaces [PDF]

open access: yes, 2010
The availability of a large, freely redistributable set of high-quality annotated images is critical to allowing researchers in the area of automatic annotation, generic object recognition and concept detection to compare results. The recent introduction
Hare, Jonathan, Lewis, Paul
core  

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

open access: yesFEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes   +32 more
wiley   +1 more source

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