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

Constructing and Visualizing Models using Mime-based Machine-learning Framework06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

2.3K
Mime is a flexible computational framework to construct a machine learning-based integration model with elegant performance. Here, we provide a detailed step-by-step procedure for developing predictive models with high accuracy, leveraging complex datasets to identify critical genes associated with disease progression, patient outcomes, and therapeutic response.
2.3K
Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

819
This research aimed to make a comparison between L1-L2-English and L1-L2 Portuguese to check how much the effect of a foreign accent accounts for both metrics and prosodic-acoustic parameters, as well as for the choice of the target voice in a voice...
819
Convolution Properties II01:17

Convolution Properties II

580
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
580
Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

13.0K
We describe a protocol for the label-free identification of lymphocyte subtypes using quantitative phase imaging and a machine learning algorithm. Measurements of 3D refractive index tomograms of lymphocytes present 3D morphological and biochemical information for individual cells, which is then analyzed with a machine-learning algorithm for identification of cell...
13.0K
Convolution Properties I01:20

Convolution Properties I

559
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
559
Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model08:20

Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model

2.5K
Worldwide medical blood parasites were automatically screened using simple steps on a low-code AI platform. The prospective diagnosis of blood films was improved by using an object detection and classification method in a hybrid deep learning model. The collaboration of active monitoring and well-trained models helps to identify hotspots of trypanosome...
2.5K

You might also read

Related Articles

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

Sort by
Same author

Icariin improves metabolic response to exercise by promoting TFEB-dependent mitochondrial clearance and metabolic reprogramming in C57BL/6 mice and C2C12 myotubes.

Frontiers in nutrition·2026
Same author

Alterations in gut microbiota and metabolic profiling are associated with papillary thyroid cancer and BRAF<sup>V600E</sup> mutation.

Endocrine·2026
Same author

Understanding overtaking risk evolution patterns and their influencing factors based on trajectory data.

Accident; analysis and prevention·2026
Same author

Alkyl-chain engineering of berberine-based amphiphilic AIE photosensitizers for dual-model antifungal phototherapy.

Journal of photochemistry and photobiology. B, Biology·2026
Same author

Towards a Cytometry Foundation Model: Interpretable Sample-level Predictive Modelling via Pretrained Transformers.

bioRxiv : the preprint server for biology·2026
Same author

Enhanced X-ray image denoising via the synergy of linear attention and convolution.

Journal of X-ray science and technology·2026

Related Experiment Video

Updated: Jan 19, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.3K

Learning Part-based Convolutional Features for Person Re-Identification.

Yifan Sun, Liang Zheng, Yali Li

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |September 11, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a part-based convolutional baseline (PCB) for person re-identification, enhancing feature discriminability. A refined part pooling (RPP) method further improves part localization and consistency, boosting overall performance.

    More Related Videos

    Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
    09:09

    Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

    Published on: September 27, 2024

    819
    Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
    08:58

    Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

    Published on: November 19, 2018

    13.0K

    Related Experiment Videos

    Last Updated: Jan 19, 2026

    Constructing and Visualizing Models using Mime-based Machine-learning Framework
    06:19

    Constructing and Visualizing Models using Mime-based Machine-learning Framework

    Published on: July 22, 2025

    2.3K
    Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
    09:09

    Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

    Published on: September 27, 2024

    819
    Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
    08:58

    Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

    Published on: November 19, 2018

    13.0K

    Area of Science:

    • Computer Vision
    • Machine Learning
    • Artificial Intelligence

    Background:

    • Pedestrian image description benefits from fine-grained, part-level features.
    • Learning discriminative features is crucial for accurate person re-identification.

    Purpose of the Study:

    • To develop a part-informed feature learning method for person re-identification.
    • To introduce a novel approach for refining part localization and enhancing feature consistency.

    Main Methods:

    • Part-based Convolutional Baseline (PCB) learns part-level features adaptable to various partitioning strategies.
    • Refined Part Pooling (RPP) re-assigns outlier pixels to improve within-part consistency without requiring part labels.
    • Weakly supervised training enables RPP to enhance existing PCB models.

    Main Results:

    • PCB descriptors demonstrate significantly higher discriminative ability compared to global descriptors.
    • RPP further boosts PCB performance by refining part localization and increasing within-part consistency.
    • On the Market-1501 dataset, achieved competitive results with (77.4+4.2)% mAP and (92.3+1.5)% rank-1 accuracy.

    Conclusions:

    • Part-level feature learning, particularly with PCB and RPP, offers a powerful approach for person re-identification.
    • RPP effectively enhances feature representation by improving part localization and consistency.
    • The proposed methods achieve state-of-the-art performance on benchmark datasets.