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

Classification of Skeletal Muscle Fibers

Classification of Skeletal Muscle Fibers

Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
Slow-Twitch Muscle Fibers
Slow oxidative, muscle fibers appear red due to large numbers of capillaries and high levels of...

Avoidance Learning and Learned Helplessness

Avoidance Learning and Learned Helplessness

Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...

Self-Evaluation: Self-Enhancement and Self-Verification

Self-Evaluation: Self-Enhancement and Self-Verification

Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...

Learning Disabilities

Learning Disabilities

Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
Dyslexia
Dyslexia is a...

Associative Learning

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...

Purposive Learning

Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...

You might also read

Related Articles

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

Sort by

Same author

Unilateral biportal endoscopic lumbar interbody fusion: Radiographic and clinical outcomes in grade I lumbar spondylolisthesis.

Medicine·2026

Same author

A Sustainable Organic Memristor with Tunable Switching for Logic Operations and Medical Image Encryption.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same author

Flexible Capacitive Pressure Sensors with Ultrasonically Engineered Cu-Filled PDMS Dielectric Layers.

Sensors (Basel, Switzerland)·2026

Same author

Comparative efficacy and safety of pathway-targeted pharmacotherapies for Alzheimer's disease: A systematic review and network meta-analysis of phase III trials.

Ageing research reviews·2026

Same author

Immune-driven induction of miR-501-5p by IL-17A enhances colorectal cancer progression.

Translational cancer research·2026

Same author

MMP7-Triggered mitophagy by regulating parkin-mediated ubiquitination of VDAC1 confers anoikis resistance in the epithelium of hyperplastic prostate.

Cell death & disease·2026

Search research articles

Related Experiment Video

Updated: Jan 23, 2026

High-resolution Fiber-optic Microendoscopy for in situ Cellular Imaging

High-resolution Fiber-optic Microendoscopy for in situ Cellular Imaging

Published on: January 11, 2011

Fiber bundle imaging resolution enhancement using deep learning.

Jianbo Shao, Junchao Zhang, Rongguang Liang

|June 6, 2019

Summary

This summary is machine-generated.

We developed a deep learning method to enhance image resolution from fiber bundle imaging. This technique uses neural networks for alignment and 3D convolution to significantly improve spatial resolution in imaging systems.

More Related Videos

Stereocilia Bundle Imaging with Nanoscale Resolution in Live Mammalian Auditory Hair Cells

Stereocilia Bundle Imaging with Nanoscale Resolution in Live Mammalian Auditory Hair Cells

Published on: January 21, 2021

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis

Published on: October 17, 2016

Related Experiment Videos

Last Updated: Jan 23, 2026

High-resolution Fiber-optic Microendoscopy for in situ Cellular Imaging

High-resolution Fiber-optic Microendoscopy for in situ Cellular Imaging

Published on: January 11, 2011

Stereocilia Bundle Imaging with Nanoscale Resolution in Live Mammalian Auditory Hair Cells

Stereocilia Bundle Imaging with Nanoscale Resolution in Live Mammalian Auditory Hair Cells

Published on: January 21, 2021

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis

Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis

Published on: October 17, 2016

Area of Science:

Biomedical Imaging
Computer Vision
Machine Learning

Background:

Fiber bundle imaging systems often face limitations in spatial resolution.
Achieving high-resolution images is crucial for detailed analysis in various scientific fields.

Purpose of the Study:

To develop and evaluate a deep learning-based method for estimating high-resolution images from multiple fiber bundle image sequences.
To significantly improve the spatial resolution of fiber bundle imaging systems.

Main Methods:

A motion estimation neural network was employed to align raw fiber bundle image sequences.
A 3D convolution neural network was utilized to learn the mapping from aligned sequences to ground truth high-resolution images.

Main Results:

The proposed deep learning method demonstrated significant improvements in spatial resolution.
Evaluations were conducted using lens tissue samples and a 1951 USAF resolution target.

Conclusions:

The developed deep learning approach effectively enhances spatial resolution in fiber bundle imaging.
This method offers a promising solution for obtaining high-resolution images from existing fiber bundle imaging systems.