Literals
- ou:codigoRevista
- 1558-0644
- 0196-2892
- dcterms:coverage
- 1980-2022
- vcard:country-name
- United States
- ou:categoriaSJR
- Electrical and Electronic Engineering (Q1)
- Earth and Planetary Sciences (miscellaneous) (Q1)
- bibo:eissn
- 1558-0644
- dcterms:identifier
- 2022-10661
- bibo:issn
- 0196-2892
- dcterms:publisher
- Institute of Electrical and Electronics Engineers Inc.
- vcard:region
- Northern America
- ou:sjrMejorCuartil
- Q1
- dcterms:title
- IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Typed Literals
- ou:sjr
- 2.400 (http://www.w3.org/2001/XMLSchema#Decimal)
Inverse Relations
- Has related:
ou:publicadaEnRevista
- Lightweight Tensorized Neural Networks for Hyperspectral Image Classification
- Accelerating Convolutional Neural Network-Based Hyperspectral Image Classification by Step Activation Quantization
- DFLLR: Deep Feature Learning with Latent Relationship Embedding for Remote Sensing Image Retrieval
- DRFL-VAT: Deep Representative Feature Learning With Virtual Adversarial Training for Semisupervised Classification of Hyperspectral Image
- DS<sup>4</sup>L: Deep Semisupervised Shared Subspace Learning for Hyperspectral Image Classification
- DisOptNet: Distilling Semantic Knowledge From Optical Images for Weather-Independent Building Segmentation
- Enhanced Spatiotemporal Fusion via MODIS-Like Images
- Ensemble Entropy Metric for Hyperspectral Anomaly Detection
- Fast Orthogonal Projection for Hyperspectral Unmixing
- Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image Classification
- Hashing for Localization (HfL): A Baseline for Fast Localizing Objects in a Large-Scale Scene
- Hyperspectral Anomaly Detection With Relaxed Collaborative Representation
- Hyperspectral Anomaly Detection Using the Spectral-Spatial Graph
- Hyperspectral and LiDAR Data Classification Using Joint CNNs and Morphological Feature Learning
- Learning Orientation Information From Frequency-Domain for Oriented Object Detection in Remote Sensing Images
- CNN-Based Hyperspectral Pansharpening with Arbitrary Resolution
- Local Semantic Feature Aggregation-Based Transformer for Hyperspectral Image Classification
- MO-CNN: Multiobjective Optimization of Convolutional Neural Networks for Hyperspectral Image Classification
- Moving Ship Optimal Association for Maritime Surveillance: Fusing AIS and Sentinel-2 Data
- Multiple Attention-Guided Capsule Networks for Hyperspectral Image Classification
- Multisource Data Reconstruction-Based Deep Unsupervised Hashing for Unisource Remote Sensing Image Retrieval
- Pseudo Complex-Valued Deformable ConvLSTM Neural Network with Mutual Attention Learning for Hyperspectral Image Classification
- Revisiting Deep Hyperspectral Feature Extraction Networks via Gradient Centralized Convolution
- Revisiting SLIC: Fast Superpixel Segmentation of Marine SAR Images Using Density Features
- Rotation-Invariant Deep Embedding for Remote Sensing Images
- Self-Supervised Robust Deep Matrix Factorization for Hyperspectral Unmixing
- Ship Detection in SAR Images by Aggregating Densities of Fisher Vectors: Extension to a Global Perspective
- Spectral-Spatial Hyperspectral Unmixing Using Nonnegative Matrix Factorization
- SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers
- Superpixel-Based Collaborative and Low-Rank Regularization for Sparse Hyperspectral Unmixing
- Variable Subpixel Convolution Based Arbitrary-Resolution Hyperspectral Pansharpening