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

Interpretations of Partial Derivatives

Interpretations of Partial Derivatives

A surface defined by a function of two variables can be visualized as a vast, uneven terrain, where each point is identified using Cartesian coordinates. The elevation of the terrain at any point is determined by a function that assigns a height value to every pair of horizontal coordinates. This representation allows the surface to be studied in terms of how its height varies across different directions.At a specific point on this terrain, understanding how the height changes requires...

You might also read

Related Articles

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

Sort by

Same author

Adsorption Behavior of Methylene Blue, Cd<sup>2+</sup>, and Pb<sup>2+</sup> Onto Raw Bamboo Shoot Brown Powder: Kinetic, Isotherm, Thermodynamic, and Regeneration Studies.

Water environment research : a research publication of the Water Environment Federation·2026

Same author

A green and facile modification of red mud waste with MIL-100 (Fe) for multi-pollutant adsorption from wastewater: isotherms, kinetics, and thermodynamics.

RSC advances·2026

Same author

Developmentally Supportive and Family Participatory Care in Special Newborn Care Units: A Review of Global Evidence, Implementation Models, and the Indian Context.

Annals of African medicine·2026

Same author

Sustainable production of microalgal nanoparticles through green synthesis towards cancer treatment.

Frontiers in bioengineering and biotechnology·2025

Same author

Role of biofilm activity on novel interwoven lattice-shaped 3D printed biocarrier for enhanced removal of organics and nutrients with reduced footprint: Performance assessment and microbial community dynamics.

Bioresource technology·2025

Same author

Redefining Risk, Biomarkers, and Precision Therapy for Hereditary Ovarian Cancer: A Review.

ACS omega·2025

Search research articles

Related Experiment Video

Updated: Jul 13, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

A semantic segmentation framework with UNet-pyramid for landslide prediction using remote sensing data.

Arush Kaushal¹, Ashok Kumar Gupta², Vivek Kumar Sehgal³

¹Jaypee University of Information Technology, Computer Science, Solan, 173234, India. arushkaushal0115@gmail.com.

Scientific Reports

|December 3, 2024

Summary

This study introduces a hybrid deep learning model for automated landslide detection using satellite imagery. The UNet-Pyramid model significantly improves detection accuracy, aiding in disaster prevention and mitigation efforts.

Keywords:

Deep Neural Network (DNN)Hybrid Model Landslide Landslide Prediction Machine Learning

More Related Videos

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Related Experiment Videos

Last Updated: Jul 13, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Area of Science:

Geosciences
Remote Sensing
Artificial Intelligence

Background:

Landslides are frequent global disasters threatening lives and infrastructure.
Traditional landslide detection methods face limitations in efficiency and data applicability.
Advancements in deep learning offer superior alternatives for landslide detection.

Purpose of the Study:

To develop a novel, automated landslide detection methodology.
To enhance landslide detection accuracy using a hybrid deep learning approach.
To mitigate the impact of landslides through improved early detection.

Main Methods:

A hybrid U-Net model integrated with pyramid pooling layers and OBIA technique was developed.
High-resolution satellite images from the Landslide4Sense dataset were utilized.
The UNet-Pyramid model was trained and validated using labeled landslide imagery.

Main Results:

The UNet-Pyramid model achieved high performance in landslide detection.
Precision: 91%, Recall: 84%, F1 Score: 87% demonstrate model efficacy.
Integration of pyramid pooling and OBIA enhanced feature acquisition and model attention.

Conclusions:

The proposed UNet-Pyramid model offers an effective automated solution for landslide detection.
This hybrid deep learning approach shows significant advantages over traditional methods.
The methodology contributes to improved landslide disaster prevention and mitigation strategies.