Biodiversity image retrieval framework for monogeneans

about

Automated identification of Monogeneans using digital image processing and K-nearest neighbour approaches.Fish Ontology framework for taxonomy-based fish recognition.A model of a digital biological ecosystem

P2860

Q36268823-BCDF5F50-A912-4F91-9D36-0B4893F3A5FD Q41722913-02401489-DA63-4908-A2F6-79ABAB7AEC64 Q58840886-B662034B-DBB5-4F69-BE06-08146E8FE5AE

P2860

Biodiversity image retrieval framework for monogeneans

Item

http://www.wikidata.org/entity/Q58840893

description

wetenschappelijk artikel

@nl

наукова стаття, опублікована в березні 2013

@uk

name

Biodiversity image retrieval framework for monogeneans

@en

Biodiversity image retrieval framework for monogeneans

@nl

type

Item

label

Biodiversity image retrieval framework for monogeneans

@en

Biodiversity image retrieval framework for monogeneans

@nl

prefLabel

Biodiversity image retrieval framework for monogeneans

@en

Biodiversity image retrieval framework for monogeneans

@nl

P1476

Biodiversity image retrieval framework for monogeneans

@en

P2093

Amandeep S. Sidhu

http://www.w3.org/2001/XMLSchema#string

Arpah Abu

http://www.w3.org/2001/XMLSchema#string

S. L. H. Lim

http://www.w3.org/2001/XMLSchema#string

Sarinder K. Dhillon

http://www.w3.org/2001/XMLSchema#string

P2860

Image Retrieval: Current Techniques, Promising Directions, and Open Issues

Knowledge-driven multidimensional indexing structure for biomedical media database retrieval.

SPIRS: a Web-based image retrieval system for large biomedical databases

Diplectanocotyla Yamaguti, 1953 (Monogenea: Diplectanoidea) from Megalops cyprinoides (Broussonet) (Teleostei: Megalopidae) off Peninsular Malaysia.

Annotation and retrieval of clinically relevant images

A review of content-based image retrieval systems in medical applications-clinical benefits and future directions.

Improving performance of content-based image retrieval schemes in searching for similar breast mass regions: an assessment.

Using relevance feedback to reduce the semantic gap in content-based image retrieval of mammographic masses.

Automatic identification of human helminth eggs on microscopic fecal specimens using digital image processing and an artificial neural network.

P304

19-33

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1080/14772000.2012.761655

http://www.w3.org/2001/XMLSchema#string

P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P577

2013-03-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P921

biodiversity

Biodiversity image retrieval framework for monogeneans

about

P2860

P2860

Biodiversity image retrieval framework for monogeneans

description

name

type

label

prefLabel

P1433

P1476

P2093

P2860

P304

P31

P356

P433

P478

P577

P921

P356

P1433

P1476

P2093

P2860

P304

P31

P356

P433

P478

P577

P921