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

Encoding01:19

Encoding

208
Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
208
Lenz's Law01:15

Lenz's Law

4.0K
The direction in which the induced emf drives the current around a wire loop can be found through the negative sign. However, it is usually easier to determine this direction with Lenz's law, named in honor of its discoverer, Heinrich Lenz (1804–1865). Lenz's law states that the direction of the induced emf drives the current around a wire loop always to oppose the change in magnetic flux that causes the emf.
If a bar magnet is moved toward a coil such that the magnetic flux...
4.0K
Leaky Scanning02:28

Leaky Scanning

5.2K
During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
5.2K
Doppler Effect - II01:05

Doppler Effect - II

3.4K
The Doppler effect has several practical, real-world applications. For instance, meteorologists use Doppler radars to interpret weather events based on the Doppler effect. Typically, a transmitter emits radio waves at a specific frequency toward the sky from a weather station. The radio waves bounce off the clouds and precipitation and travel back to the weather station. The radio frequency of the waves reflected back to the station appears to decrease if the clouds or precipitation are moving...
3.4K
Downsampling01:20

Downsampling

192
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...
192
Doppler Effect - I00:56

Doppler Effect - I

3.6K
The Doppler effect and Doppler shift were named after the Austrian physicist and mathematician Christian Johann Doppler in 1842, who conducted experiments with both moving sources and moving observers. Consider an observer standing on a street corner, observing an ambulance with a siren sound passing by at a constant speed. The observer experiences two characteristic changes in the sound of the siren. Initially, the sound increases in loudness as the ambulance approaches and decreases in...
3.6K

You might also read

Related Articles

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

Sort by
Same author

Recent Advancements in Learning Algorithms for Point Clouds: An Updated Overview.

Sensors (Basel, Switzerland)·2022
Same author

Advanced Assistive Maintenance Based on Augmented Reality and 5G Networking.

Sensors (Basel, Switzerland)·2020
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jul 24, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.6K

CACTUS: Content-Aware Compression and Transmission Using Semantics for Automotive LiDAR Data.

Daniele Mari1, Elena Camuffo1, Simone Milani1

  • 1Department of Information Engineering, University of Padova, Via Gradenigo 6/A, 35131 Padova, Italy.

Sensors (Basel, Switzerland)
|July 8, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces Content-Aware Compression and Transmission Using Semantics (CACTUS) for efficient automotive LiDAR data transmission. CACTUS optimizes data transfer by leveraging semantic information, improving compression and speed.

Keywords:
LiDARcompressionpoint cloudssemantic segmentationtransmission

More Related Videos

Author Spotlight: Advancing Understanding of Age-Related Lens Stiffness Changes
05:19

Author Spotlight: Advancing Understanding of Age-Related Lens Stiffness Changes

Published on: April 5, 2024

2.4K
Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.7K

Related Experiment Videos

Last Updated: Jul 24, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.6K
Author Spotlight: Advancing Understanding of Age-Related Lens Stiffness Changes
05:19

Author Spotlight: Advancing Understanding of Age-Related Lens Stiffness Changes

Published on: April 5, 2024

2.4K
Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.7K

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Automotive Technology

Background:

  • Automotive applications increasingly rely on cloud/edge computing, necessitating the transmission of large Light Detection and Ranging (LiDAR) datasets.
  • Effective Point Cloud (PC) compression is vital for preserving semantic information crucial for scene understanding in autonomous systems.
  • Current methods treat segmentation and compression independently, overlooking the potential of semantic importance for data transmission optimization.

Purpose of the Study:

  • To develop a novel framework, Content-Aware Compression and Transmission Using Semantics (CACTUS), for optimizing automotive LiDAR data transmission.
  • To investigate the use of semantic information to guide data transmission and improve Point Cloud compression efficiency.
  • To enhance the speed and flexibility of data compression codecs by incorporating semantic awareness.

Main Methods:

  • Proposed the CACTUS coding framework, which partitions Point Cloud data based on semantic information into separate streams.
  • Implemented independent coding of semantically consistent point sets to preserve class-specific information.
  • Evaluated the impact of semantic information on data transmission and compression efficiency compared to traditional methods.

Main Results:

  • Experimental results demonstrate that independent coding of semantically consistent point sets effectively preserves class information.
  • The CACTUS strategy shows significant gains in compression efficiency when semantic information is transmitted.
  • CACTUS improves the overall speed and flexibility of the baseline data compression codec.

Conclusions:

  • CACTUS offers an effective approach to optimize automotive LiDAR data transmission by exploiting semantic information.
  • Leveraging semantic awareness in compression frameworks leads to improved efficiency and preserves critical scene understanding data.
  • The proposed method enhances existing codecs, paving the way for more efficient automotive data processing and communication.