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

Upsampling01:22

Upsampling

214
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
214
Downsampling01:20

Downsampling

135
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
135
Deconvolution01:20

Deconvolution

139
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
139
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

63
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
63
Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

49
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
49
Convolution Properties II01:17

Convolution Properties II

176
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...
176

You might also read

Related Articles

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

Sort by
Same author

Microbial photoelectrotrophic denitrification: Development, mechanisms, and applications in wastewater treatment.

Bioresource technology·2026
Same author

Roles and applications of artificial intelligence in fetal and placental MRI: a literature review.

BMC pregnancy and childbirth·2026
Same author

BiOBr/g-C<sub>3</sub>N<sub>4</sub> Planar Heterostructures toward Enhanced Tetracycline Hydrochloride Removal.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

Application of retrograde distal perfusion via posterior tibial artery in venoarterial extracorporeal membrane oxygenation: A retrospective single-center study.

JTCVS techniques·2026
Same author

Metagenomic characterization of the virome of Aedes albopictus in Anhui Province, China, with phylogenetic analysis of CRESS-DNA viruses and Parvoviridae.

Virus genes·2026
Same author

Network and machine learning analysis of childhood trauma, mental health, and AI-based emotional support needs in adolescents from underdeveloped regions.

BMC psychology·2026
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: Jun 12, 2025

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

369

A Versatile Point Cloud Compressor Using Universal Multiscale Conditional Coding - Part I: Geometry.

Jianqiang Wang, Ruixiang Xue, Jiaxin Li

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |September 17, 2024
    PubMed
    Summary
    This summary is machine-generated.

    Unicorn, a new point cloud compression framework, efficiently compresses geometry and attributes using multiscale sparse tensors. This learning-based solution offers state-of-the-art compression for diverse point clouds.

    More Related Videos

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    377
    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
    11:38

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

    Published on: August 23, 2017

    9.8K

    Related Experiment Videos

    Last Updated: Jun 12, 2025

    Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
    09:19

    Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

    Published on: April 18, 2025

    369
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    377
    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
    11:38

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

    Published on: August 23, 2017

    9.8K

    Area of Science:

    • Computer Vision
    • Data Compression
    • 3D Data Processing

    Background:

    • Point cloud data is increasingly prevalent in 3D applications.
    • Existing compression methods face challenges with diverse point cloud characteristics and real-time performance.
    • Efficient compression is crucial for storage, transmission, and rendering of 3D data.

    Purpose of the Study:

    • To introduce Unicorn, a universal multiscale conditional coding framework for point cloud compression.
    • To address both geometry and attribute compression in a unified approach.
    • To achieve superior compression efficiency compared to existing methods.

    Main Methods:

    • Constructing multiscale sparse tensors for voxelized point cloud frames.
    • Leveraging lower-scale priors from current and reference frames for predictive reconstruction.
    • Employing a learning-based approach for versatile compression (lossy/lossless).

    Main Results:

    • Unicorn significantly outperforms standard-compliant (MPEG G-PCC, V-PCC) and learning-based solutions.
    • Achieved state-of-the-art compression efficiency across diverse point cloud types.
    • Demonstrated affordable complexity suitable for practical applications.

    Conclusions:

    • Unicorn provides a versatile and highly efficient solution for point cloud compression.
    • The framework's multiscale conditional coding approach enables superior performance.
    • Unicorn represents a significant advancement in 3D data compression technology.