Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

5.3K
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...
5.3K
The Retinoblastoma Gene01:20

The Retinoblastoma Gene

4.2K
Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
The first-ever tumor suppressor gene called Rb was identified in retinoblastoma - a rare eye tumor in children. In inherited forms of the disease, a child inherits one defective copy of the Rb gene, which predisposes them to retinoblastoma. However,...
4.2K
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.2K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.2K

You might also read

Related Articles

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

Sort by
Same author

EvoPS: Evolutionary Patch Selection in the Training Embedding Space of Whole Slide Images.

Artificial intelligence in medicine·2026
Same author

Multimodal learning for scalable representation of high-dimensional medical data.

Frontiers in digital health·2026
Same author

Mitigating data center bias in cancer classification: Transfer bias unlearning and feature size reduction via conflict-of-interest free multi-objective optimization.

Artificial intelligence in medicine·2026
Same author

Foundation Models for Histopathology-Fanfare or Flair.

Mayo Clinic proceedings. Digital health·2025
Same author

Investigation on potential bias factors in histopathology datasets.

Scientific reports·2025
Same author

Validation of histopathology foundation models through whole slide image retrieval.

Scientific reports·2025
Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026
Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026
Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026
Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026
Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026
Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Sep 12, 2025

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples
08:18

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Published on: April 7, 2023

1.7K

Enhancing image retrieval through optimal barcode representation.

Rasa Khosrowshahli1, Farnaz Kheiri2, Azam Asilian Bidgoli3

  • 1Faculty of Mathematics and Science, Brock University, St. Catharines, ON, L2S 3A1, Canada.

Scientific Reports
|August 6, 2025
PubMed
Summary
This summary is machine-generated.

Optimizing feature sequences for binary barcodes significantly improves image retrieval accuracy. This research enhances deep learning-based barcode generation for efficient data processing and memory efficiency in machine learning applications.

Keywords:
Barcode OptimizationCombinatorial OptimizationGenetic AlgorithmHistopathologyImage RetrievalOrder of FeaturesRadiology

More Related Videos

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray
09:05

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray

Published on: January 6, 2016

14.7K
Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications
13:14

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Published on: April 14, 2015

9.4K

Related Experiment Videos

Last Updated: Sep 12, 2025

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples
08:18

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Published on: April 7, 2023

1.7K
Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray
09:05

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray

Published on: January 6, 2016

14.7K
Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications
13:14

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Published on: April 14, 2015

9.4K

Area of Science:

  • Machine Learning
  • Computer Vision
  • Data Science

Background:

  • Binary encoding optimizes data processing and memory efficiency in machine learning.
  • Deep barcoding generates binary codes from deep learning features for image retrieval.
  • Converting high-dimensional features to compact binary codes remains a challenge.

Purpose of the Study:

  • To address the combinatorial challenge in difference-based feature binarization.
  • To optimize feature sequences for improved retrieval performance.
  • To enhance the accuracy and efficiency of image retrieval using binary barcodes.

Main Methods:

  • Optimized feature sequences based on retrieval performance metrics.
  • Evaluated the approach on medical (TCGA, COVID-19 X-rays) and non-medical (CIFAR, Fashion-MNIST) image datasets.
  • Compared performance against arbitrary or default feature orderings.

Main Results:

  • Identified optimal feature orderings leading to substantial improvements in retrieval effectiveness.
  • Demonstrated significant enhancement in accuracy for fast image retrieval.
  • Showcased the applicability of optimized binary barcodes across diverse domains.

Conclusions:

  • Optimizing binary barcode representation is crucial for enhancing image retrieval accuracy.
  • The proposed method offers a significant advancement over existing techniques.
  • Binary barcodes hold considerable potential for various applications requiring efficient image retrieval.