NDLI: Sea-Land Segmentation of Remote Sensing Images Based on SDW-UNet

Please wait, while we are loading the content...

Computer Modeling in Engineering & Sciences (CMES)

Computer Systems Science and Engineering (CSSE)

Year: 2024 Volume: 48

Year: 2023 Volume: 47

Year: 2023 Volume: 46

Year: 2023 Volume: 45

A Framework of Deep Learning and Selection-Based Breast Cancer Detection from Histopathology Images

Breast Cancer Diagnosis Using Feature Selection Approaches and Bayesian Optimization

Sea-Land Segmentation of Remote Sensing Images Based on SDW-UNet

Effective and Efficient Video Compression by the Deep Learning Techniques

Intelligent Home Using Fuzzy Control Based on AIoT

Feature Matching Combining Variable Velocity Model with Reverse Optical Flow

A Secure Framework for Blockchain Transactions Protection

Sentiment Analysis with Tweets Behaviour in Twitter Streaming API

Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

An Enhanced Group Key-Based Security Protocol to Protect 5G SON Against FBS

De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning (MCR)

Cooperative NOMA Based on OAM Transmission for Beyond 5G Applications

Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

Optimizing Storage for Energy Conservation in Tracking Wireless Sensor Network Objects

Adaptive Deep Learning Model for Software Bug Detection and Classification

Competitive Multi-Verse Optimization with Deep Learning Based Sleep Stage Classification

Genetic-based Fuzzy IDS for Feature Set Reduction and Worm Hole Attack Detection

Optimized Deep Learning Model for Effective Spectrum Sensing in Dynamic SNR Scenario

Intrusion Detection Using Federated Learning for Computing

Profiling of Urban Noise Using Artificial Intelligence

Optimized Resource Allocation and Queue Management for Traffic Control in MANET

Neighborhood Search Based Improved Bat Algorithm for Web Service Composition

Covid-19 Diagnosis Using a Deep Learning Ensemble Model with Chest X-Ray Images

DERNNet: Dual Encoding Recurrent Neural Network Based Secure Optimal Routing in WSN

Search and Rescue Optimization with Machine Learning Enabled Cybersecurity Model

Image Enhancement Using Adaptive Fractional Order Filter

Radial Basis Approximations Based BEMD for Enhancement of Non-Uniform Illumination Images

Leveraging Readability and Sentiment in Spam Review Filtering Using Transformer Models

A Machine Learning Approach for Artifact Removal from Brain Signal

Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

PSO-DBNet for Peak-to-Average Power Ratio Reduction Using Deep Belief Network

Real Time Automation and Ratio Control Using PLC & SCADA in Industry 4.0

Resource Allocation Based on SFLA Algorithm for D2D Multicast Communications

Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Copy Move Forgery Detection Using Novel Quadsort Moth Flame Light Gradient Boosting Machine

An Optimized Method for Accounting Information in Logistic Systems

Energy Proficient Reduced Coverage Set with Particle Swarm Optimization for Distributed Sensor Network

Wrapper Based Linear Discriminant Analysis (LDA) for Intrusion Detection in IIoT

Improved Metaheuristic Based Failure Prediction with Migration Optimization in Cloud Environment

Liver Tumors Segmentation Using 3D SegNet Deep Learning Approach

Hybrid Metaheuristics Feature Selection with Stacked Deep Learning-Enabled Cyber-Attack Detection Model

Fast Mesh Reconstruction from Single View Based on GCN and Topology Modification

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

DoS Attack Detection Based on Deep Factorization Machine in SDN

Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries

Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-Hop Routing Protocol

Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

Optimized Resource Allocation for IoT-D2D Communication Using WSN

Year: 2023 Volume: 44

Year: 2022 Volume: 43

Year: 2022 Volume: 42

Year: 2022 Volume: 41

Year: 2022 Volume: 40

Year: 2021 Volume: 39

Year: 2021 Volume: 38

Year: 2021 Volume: 37

Year: 2021 Volume: 36

Year: 2020 Volume: 35

Year: 2019 Volume: 34

Year: 2018 Volume: 33

Computers, Materials & Continua (CMC)

Congenital Heart Disease (CHD)

Digital Engineering and Digital Twin (DEDT)

Energy Engineering (ENERGY)

Fluid Dynamics & Materials Processing (FDMP)

Frontiers in Heat and Mass Transfer (FHMT)

Intelligent Automation & Soft Computing (IASC)

International Journal of Mental Health Promotion (IJMHP)

Journal of Blockchain and Intelligent Computing (JBIC)

Journal of Cyber Security (JCS)

Journal of Information Hiding and Privacy Protection (JIHPP)

Journal of Intelligent Medicine and Healthcare (JIMH)

Journal of New Media (JNM)

Journal of Polymer Materials (JPM)

Journal of Quantum Computing (JQC)

Journal of Renewable Materials (JRM)

Journal on Artificial Intelligence (JAI)

Journal on Big Data (JBD)

Journal on Internet of Things (JIOT)

Oncology Research (OR)

Phyton-International Journal of Experimental Botany (PHYTON)

Structural Durability & Health Monitoring (SDHM)

Sea-Land Segmentation of Remote Sensing Images Based on SDW-UNet

Content Provider	Tech Science Press
Author	Chen, Shanji Ma, Ying Liu, Pengyu Gao, Qian Jia, Xiaowei Liu, Tianyu
Abstract	Image segmentation of sea-land remote sensing images is of great importance for downstream applications including shoreline extraction, the monitoring of near-shore marine environment, and near-shore target recognition. To mitigate large number of parameters and improve the segmentation accuracy, we propose a new Squeeze-Depth-Wise UNet (SDW-UNet) deep learning model for sea-land remote sensing image segmentation. The proposed SDW-UNet model leverages the squeeze-excitation and depth-wise separable convolution to construct new convolution modules, which enhance the model capacity in combining multiple channels and reduces the model parameters. We further explore the effect of position-encoded information in NLP (Natural Language Processing) domain on sea-land segmentation task. We have conducted extensive experiments to compare the proposed network with the mainstream segmentation network in terms of accuracy, the number of parameters and the time cost for prediction. The test results on remote sensing data sets of Guam, Okinawa, Taiwan, San Diego, and Diego Garcia demonstrate the effectiveness of SDW-UNet in recognizing different types of sea-land areas with a smaller number of parameters, reduces prediction time cost and improves performance over other mainstream segmentation models. We also show that the position encoding can further improve the accuracy of model segmentation.
Related Links	https://www.techscience.com/csse/v45n2/50380
Starting Page	1033
Ending Page	1045
ISSN	02676192
DOI	10.32604/csse.2023.028225
Issue Number	2
Journal	Computer Systems Science and Engineering (CSSE)
Volume Number	45
Language	English
Publisher Date	2022-11-03
Access Restriction	Open
Subject Keyword	UNet depth-wise separable convolution Sea-land segmentation squeeze-excitation position encoding
Content Type	Text
Resource Type	Article
Subject	Computer Science

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in