Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Encoding

Encoding

Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...

Imaging Biological Samples with Optical Microscopy

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Blister fluid and serum cytokine levels in severe sepsis in humans reflect skin dysfunction.

Acta anaesthesiologica Scandinavica·2016

Same author

Dermal expression of laminin-332 and type IV collagen in humans with severe sepsis.

Acta anaesthesiologica Scandinavica·2015

Same author

True bacteremias caused by coagulase negative Staphylococcus are difficult to distinguish from blood culture contaminants.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology·2012

Same author

Patient-reported complications associated with Campylobacter jejuni infection.

Epidemiology and infection·2009

Same author

Deep, respiratory tract and ear infections caused by Pseudallescheria (Scedosporium) and Microascus (Scopulariopsis) in Finland. A 10-year retrospective multi-center study.

Medical mycology·2009

Same author

Biofilm formation by Escherichia coli isolated from patients with urinary tract infections.

Clinical nephrology·2009

Search research articles

Related Experiment Video

Updated: Jul 7, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

PicSOM-self-organizing image retrieval with MPEG-7 content descriptors.

J Laaksonen¹, M Koskela, E Oja

¹Lab. of Comput. and Inf. Sci., Helsinki Univ. of Technol., Espoo, Finland.

IEEE Transactions on Neural Networks

|February 5, 2008

Summary

This summary is machine-generated.

This study introduces PicSOM, a novel neural network system for content-based image retrieval (CBIR). PicSOM utilizes MPEG-7 descriptors and relevance feedback (RF) to achieve high retrieval precision, outperforming traditional methods.

Related Experiment Videos

Last Updated: Jul 7, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Area of Science:

Computer Science
Artificial Intelligence
Information Retrieval

Background:

Content-based image retrieval (CBIR) has historically lacked standardized methods for describing visual content.
The MPEG-7 international standard offers a framework and specific descriptors for content description, addressing this limitation.

Purpose of the Study:

To apply MPEG-7 visual content descriptors within the PicSOM system, a neural, self-organizing technique for CBIR.
To compare the performance of the PicSOM system using MPEG-7 descriptors against a reference system based on vector quantization (VQ).

Main Methods:

Development of the PicSOM system, utilizing tree-structured self-organizing maps (SOMs) based on pictorial examples and relevance feedback (RF).
Integration and application of MPEG-7 visual content descriptors within the PicSOM architecture.
Comparative analysis against a vector quantization (VQ) based image indexing technique.

Main Results:

MPEG-7 content descriptors are compatible with the PicSOM system, despite Euclidean distance not being optimal for all descriptors.
The PicSOM system demonstrates a slower initial retrieval phase compared to the VQ reference system.
PicSOM's retrieval precision significantly surpasses the reference system once its relevance feedback (RF) mechanism is engaged.

Conclusions:

The PicSOM system effectively leverages MPEG-7 descriptors for enhanced content-based image retrieval.
The relevance feedback (RF) mechanism is crucial for PicSOM's superior retrieval precision.
PicSOM presents a viable and powerful alternative for advanced image retrieval applications.