RSLC-Deeplab: A Ground Object Classification Method for High-Resolution Remote Sensing Images
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
RSLC-Deeplab: A Ground Object Classification Method for High-Resolution Remote Sensing Images
Authors
Keywords
-
Journal
Electronics
Volume 12, Issue 17, Pages 3653
Publisher
MDPI AG
Online
2023-08-30
DOI
10.3390/electronics12173653
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An attention-fused network for semantic segmentation of very-high-resolution remote sensing imagery
- (2021) Xuan Yang et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Semantic segmentation of high-resolution remote sensing images based on a class feature attention mechanism fused with Deeplabv3+
- (2021) Zhimin Wang et al. COMPUTERS & GEOSCIENCES
- ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery
- (2021) Rui Li et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- An Improved Res-UNet Model for Tree Species Classification Using Airborne High-Resolution Images
- (2020) Kaili Cao et al. Remote Sensing
- Unmanned Aerial Vehicle for Remote Sensing Applications—A Review
- (2019) Huang Yao et al. Remote Sensing
- DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- (2018) Liang-Chieh Chen et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning
- (2018) Ronald Kemker et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- (2017) Vijay Badrinarayanan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Fast Segmentation and Classification of Very High Resolution Remote Sensing Data Using SLIC Superpixels
- (2017) Ovidiu Csillik Remote Sensing
- Segmentation of Remote Sensing Images Using Similarity-Measure-Based Fusion-MRF Model
- (2014) Tamas Sziranyi et al. IEEE Geoscience and Remote Sensing Letters
- Hybrid region merging method for segmentation of high-resolution remote sensing images
- (2014) Xueliang Zhang et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- The Performance of Random Forests in an Operational Setting for Large Area Sclerophyll Forest Classification
- (2013) Andrew Mellor et al. Remote Sensing
- Edge-Guided Multiscale Segmentation of Satellite Multispectral Imagery
- (2012) Jianyu Chen et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- A framework for the segmentation of high-resolution satellite imagery using modified seeded-region growing and region merging
- (2011) Y. Byun et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- A novel multi-threshold segmentation approach based on differential evolution optimization
- (2010) Erik Cuevas et al. EXPERT SYSTEMS WITH APPLICATIONS
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started