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

Light Acquisition

Light Acquisition

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.

Difference from Background: Limit of Detection

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...

The Y-to-Delta Circuit

The Y-to-Delta Circuit

A balanced wye-to-delta circuit comprises balanced Y-connected voltage sources and delta-connected loads with no neutral line connection.
The initial step in analyzing a wye-to-delta circuit is to assume a positive phase sequence. These phase voltages are then utilized to calculate the line voltages that occur directly across the delta-connected load impedances. Van, Vbn, and Vcn are the phase voltages in wye, and Vab, Vbc, and Vca are the line voltages for a delta circuit. The relation between...

Voltage Doubler Circuit

Voltage Doubler Circuit

A voltage doubler circuit integrates two main components: a clamping section and a rectifier section. The clamping section consists of a capacitor (C1) and a diode (D1), whereas the rectifier section is equipped with another diode (D2) and capacitor (C2). This circuit produces an output voltage with twice the amplitude of the sinusoidal input voltage.

Color Vision

Color Vision

Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.

The Y-to-Y Circuit

The Y-to-Y Circuit

In a balanced four-wire wye-to-wye system, the arrangement involves wye-connected sinusoidal voltage sources and loads, connected through a neutral wire that links the neutral nodes of the source and load. The load impedance is connected across each phase of the load. The wye-connected source can be connected to the wye-connected load in four-wire and three-wire arrangements. A three-phase system is considered balanced when the load on each phase is equal, leading to uniform current flow and...

You might also read

Related Articles

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

Sort by

Same author

Deep Learning-Based Driver's Hands on/off Prediction System Using In-Vehicle Data.

Sensors (Basel, Switzerland)·2023

Same author

PU-MFA: Point Cloud Up-Sampling via Multi-Scale Features Attention.

Sensors (Basel, Switzerland)·2022

Same author

Multimodal Data Collection System for Driver Emotion Recognition Based on Self-Reporting in Real-World Driving.

Sensors (Basel, Switzerland)·2022

Same author

DRER: Deep Learning-Based Driver's Real Emotion Recognizer.

Sensors (Basel, Switzerland)·2021

Search research articles

Related Experiment Video

Updated: Jul 16, 2025

Light Spot-Based Assay for Analysis of Drosophila Larval Phototaxis

Light Spot-Based Assay for Analysis of Drosophila Larval Phototaxis

Published on: September 27, 2019

One-Stage Brake Light Status Detection Based on YOLOv8.

Geesung Oh¹, Sejoon Lim²

¹Graduate School of Automotive Engineering, Kookmin University, 77, Jeongneung-ro, Seongbuk-gu, Seoul 02707, Republic of Korea.

Sensors (Basel, Switzerland)

|September 9, 2023

Summary

This summary is machine-generated.

This study introduces a novel method for detecting vehicle brake light status using YOLOv8, enhancing safety and interpretability for advanced driver assistance systems (ADAS) and autonomous driving.

Keywords:

ADAS YOLOv8 autonomous brake light status one-stage detection

More Related Videos

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

Published on: October 9, 2013

Related Experiment Videos

Last Updated: Jul 16, 2025

Light Spot-Based Assay for Analysis of Drosophila Larval Phototaxis

Light Spot-Based Assay for Analysis of Drosophila Larval Phototaxis

Published on: September 27, 2019

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

Published on: October 9, 2013

Area of Science:

Computer Vision
Artificial Intelligence
Automotive Engineering

Background:

Advanced driver assistance systems (ADAS) and autonomous driving face challenges in achieving Level 3 automation.
Level 3 automation requires enhanced safety and interpretability, necessitating reliable vehicle cue detection.
Brake light status is a critical visual cue for human drivers and autonomous systems.

Purpose of the Study:

To develop a novel method for detecting driving vehicles and their brake light status.
To improve the safety, interpretability, and comfort of advanced driver assistance systems (ADAS) and autonomous driving technologies.
To provide a publicly available dataset for brake light status detection research.

Main Methods:

A fast and accurate one-stage brake light status detection network based on YOLOv8 was developed.
Transfer learning was applied using a custom dataset of over 11,000 forward images with manual annotations.
The method was evaluated for detection accuracy and inference time on an edge device (Jetson Nano).

Main Results:

The proposed YOLOv8 network accurately detects vehicles and their brake light status.
High detection performance was achieved with a mean average precision (mAP50) between 0.766 and 0.793.
Short inference time of 133.30 ms was recorded on the Jetson Nano edge device.

Conclusions:

The proposed method achieves high accuracy and fast inference for brake light status detection.
This contributes valuable input information for ADAS and autonomous driving, enhancing safety and interpretability.
The publicly available dataset supports further research in this critical area of automotive technology.