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

Binary Fission01:26

Binary Fission

3.2K
Binary fission is the primary mode of asexual reproduction in prokaryotes, such as bacteria. It results in the production of two genetically identical daughter cells. This highly efficient process ensures the rapid propagation of bacterial populations under favorable conditions and involves coordinated cellular and molecular events.DNA Replication and SeparationThe process begins with the replication of the bacterial chromosome. The circular DNA molecule unwinds at a specific origin of...
3.2K
Binary Fission01:20

Binary Fission

64.2K
Fission is the division of a single entity into two or more parts, which regenerate into separate entities that resemble the original. Organisms in the Archaea and Bacteria domains reproduce using binary fission, in which a parent cell splits into two parts that can each grow to the size of the original parent cell. This asexual method of reproduction produces cells that are all genetically identical.
64.2K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

10.0K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
10.0K
lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

3.7K
3.7K
pH Scale02:41

pH Scale

80.3K
Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
80.3K
Nursing Code of Ethics01:29

Nursing Code of Ethics

4.6K
The Nursing Code of Ethics sets the ethical benchmark for the profession, and guides nurses in ethical analysis and decision making at the societal, organizational, and clinical levels. The code encompasses showing compassion and respect for the patient, their families, and communities in all circumstances while committing to providing patient-centered care. In addition, the code states that nurses must advocate for the patient by defending a cause or recommendation to protect their rights,...
4.6K

You might also read

Related Articles

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

Sort by
Same author

Deciphering small sequence differences in T cell receptor-antigen pairing.

Nature communications·2026
Same author

Histopathology-centered Computational Evolution of Spatial Omics: Integration, Mapping, and Foundation Models.

ArXiv·2026
Same author

Multimodal analysis of whole slide images in colorectal cancer.

NPJ digital medicine·2025
Same author

Segment Any Cell: A SAM-Based Auto-Prompting Fine-Tuning Framework for Nuclei Segmentation.

IEEE transactions on neural networks and learning systems·2025
Same author

Pancancer outcome prediction via a unified weakly supervised deep learning model.

Signal transduction and targeted therapy·2025
Same author

Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction.

IEEE journal of biomedical and health informatics·2025
Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Feb 11, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.1K

Sub-Selective Quantization for Learning Binary Codes in Large-Scale Image Search.

Yeqing Li, Wei Liu, Junzhou Huang

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |May 8, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new sub-selection algorithm to efficiently learn binary codes for large-scale image search. The method significantly reduces computational costs for image retrieval, improving efficiency.

    More Related Videos

    Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
    04:09

    Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

    Published on: October 10, 2018

    8.8K
    A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
    12:18

    A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

    Published on: January 11, 2020

    8.1K

    Related Experiment Videos

    Last Updated: Feb 11, 2026

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
    07:35

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

    Published on: October 11, 2018

    8.1K
    Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
    04:09

    Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

    Published on: October 10, 2018

    8.8K
    A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
    12:18

    A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

    Published on: January 11, 2020

    8.1K

    Area of Science:

    • Computer Science
    • Machine Learning
    • Image Processing

    Background:

    • The internet's visual content explosion necessitates efficient large-scale image search.
    • Binary codes offer efficiency in image storage and similarity computation.
    • Existing binary code learning methods are computationally expensive for large datasets.

    Purpose of the Study:

    • To develop a computationally efficient algorithm for large-scale binary code learning.
    • To reduce the training costs associated with image retrieval methods.
    • To improve the performance of image search through optimized code learning.

    Main Methods:

    • A sub-selection based matrix manipulation algorithm is proposed.
    • The algorithm is applied to various linear and nonlinear quantization techniques.
    • Theoretical properties of the sub-selective quantization are mathematically proven.

    Main Results:

    • The proposed algorithm significantly reduces the computational cost of binary code learning.
    • Sub-selective quantization demonstrates theoretical validity.
    • Extensive experiments on large image benchmarks confirm the method's efficacy.

    Conclusions:

    • The sub-selection based matrix manipulation algorithm offers a computationally efficient solution for large-scale binary code learning.
    • This method enhances the efficiency of image retrieval systems.
    • The approach is theoretically sound and experimentally validated on large datasets.