On the public citation graph

EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

0 signed · 119 inferred · view as graph

Concept DOI. This identifier always resolves to the latest version of the record, currently 10.5281/zenodo.7711810. Edges are recorded against each version separately.

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_38openalex-extracted

Identity Mappings in Deep Residual Networks

inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-extracted

ImageNet Large Scale Visual Recognition Challenge

inferredcites →https://doi.org/10.1016/j.patcog.2016.07.001openalex-extracted

Towards better exploiting convolutional neural networks for remote sensing scene classification

inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-extracted

Going deeper with convolutions

inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-extracted

Rethinking the Inception Architecture for Computer Vision

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-extracted

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvprw.2015.7301382openalex-extracted

Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?

inferredcites →https://doi.org/10.1109/cvprw.2016.90openalex-extracted

Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/jstars.2017.2755672openalex-extracted

OpenSARShip: A Dataset Dedicated to Sentinel-1 Ship Interpretation

inferredcites →https://doi.org/10.1145/1869790.1869829openalex-extracted

Bag-of-visual-words and spatial extensions for land-use classification

inferredcites →https://doi.org/10.1145/2820783.2820816openalex-extracted

DeepSat

inferredcites →https://doi.org/10.1145/2964284.2984063openalex-extracted

Contextual Enrichment of Remote-Sensed Events with Social Media Streams

inferredcites →https://doi.org/10.1162/neco.1989.1.4.541openalex-extracted

Backpropagation Applied to Handwritten Zip Code Recognition

inferredcites →https://doi.org/10.1609/aaai.v31i1.11231openalex-extracted

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

inferredcites →https://doi.org/10.3390/rs10050719openalex-extracted

Training Small Networks for Scene Classification of Remote Sensing Images via Knowledge Distillation

inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-extracted

Very Deep Convolutional Networks for Large-Scale Image Recognition

inferredcites →https://doi.org/10.48550/arxiv.1502.03409openalex-extracted

Large-Scale Deep Learning on the YFCC100M Dataset

inferredcites →https://doi.org/10.48550/arxiv.1508.00092openalex-extracted

Land Use Classification in Remote Sensing Images by Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/icip.2019.8803050openalex-snapshot

Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4185660openalex-extracted

Improved Learning by Using a Modified Activation Function of a Convolutional Neural Network in Image Classification

inferred← citeshttps://doi.org/10.2139/ssrn.4526365openalex-extracted

F-Scp: An Automatic Prompt Generation Method Based on Visual Language Pre-Training Models for Specific Classes

inferred← citeshttps://doi.org/10.2139/ssrn.4627819openalex-extracted

inferred← citeshttps://doi.org/10.2139/ssrn.5063928openalex-extracted

From Tradition to Transformation: Deep and Self-Supervised Learning Approaches for Remote Sensing in Agriculture and Environmental Change

inferred← uses_datahttps://doi.org/10.5281/zenodo.15209589zenodo-depositor-declared

inferred← citeshttps://doi.org/10.1007/978-3-030-46133-1_19openalex-snapshot

Learning Disentangled Representations of Satellite Image Time Series

inferred← citeshttps://doi.org/10.1007/978-3-030-58542-6_13openalex-snapshot

Learning Disentangled Representations via Mutual Information Estimation

inferred← citeshttps://doi.org/10.1007/978-3-031-43424-2_27openalex-snapshot

Constrained-HIDA: Heterogeneous Image Domain Adaptation Guided by Constraints

inferred← citeshttps://doi.org/10.1007/s10994-023-06374-1openalex-snapshot

Learning domain invariant representations of heterogeneous image data

inferred← citeshttps://doi.org/10.1007/s12559-026-10623-5openalex-snapshot

Uncertainty Generation Meta-training for Cross-domain Few-shot Learning

inferred← citeshttps://doi.org/10.1007/s41870-025-02619-5openalex-snapshot

NB-NN-RF: an ensemble machine learning approach for classification of satellite images

inferred← citeshttps://doi.org/10.1016/j.knosys.2024.111726openalex-snapshot

Multi-modal recursive prompt learning with mixup embedding for generalization recognition

inferred← citeshttps://doi.org/10.1016/j.knosys.2025.115122openalex-snapshot

Text augmentation for vision: Modality-preference aware few-shot learning

inferred← citeshttps://doi.org/10.1016/j.knosys.2026.115517openalex-snapshot

CATE: Consensus-aware calibration for test-time prompt tuning via energy anchoring

inferred← citeshttps://doi.org/10.1016/j.neucom.2026.134512openalex-snapshot

Mixture of knowledge from multiple pre-trained foundation models for few-shot recognition

inferred← citeshttps://doi.org/10.1016/j.neunet.2025.107472openalex-snapshot

DGPrompt: Dual-guidance prompts generation for vision-language models

inferred← citeshttps://doi.org/10.1016/j.patcog.2024.110960openalex-snapshot

ZooKT: Task-adaptive knowledge transfer of Model Zoo for few-shot learning

inferred← citeshttps://doi.org/10.1080/01431161.2025.2465917openalex-snapshot

Deep Clustering of Remote Sensing Scenes through Heterogeneous Transfer Learning

inferred← citeshttps://doi.org/10.1093/oxfordhb/9780192868282.013.79openalex-snapshot

An Introduction to Neural Networks for the Social Sciences

inferred← citeshttps://doi.org/10.1109/asyu50717.2020.9259898openalex-snapshot

Evaluation of Transfer Learning Approach for Satellite Image Classification

inferred← citeshttps://doi.org/10.1109/bigdata52589.2021.9671569openalex-snapshot

CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels

inferred← citeshttps://doi.org/10.1109/icip.2019.8803050openalex-snapshot

Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks

inferred← citeshttps://doi.org/10.1109/igarss.2019.8900532openalex-snapshot

Bigearthnet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding

inferred← citeshttps://doi.org/10.1109/igarss47720.2021.9554405openalex-snapshot

Hierarchical Probabilistic Embeddings for Multi-View Image Classification

inferred← citeshttps://doi.org/10.1109/itca52113.2020.00106openalex-snapshot

MobileNetV2 Model for Image Classification

inferred← citeshttps://doi.org/10.1109/jstars.2020.2973794openalex-snapshot

2019 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 12

inferred← citeshttps://doi.org/10.1109/latincom.2018.8613216openalex-snapshot

Convolutional Neural Networks for Semantic Segmentation of Multispectral Remote Sensing Images

inferred← citeshttps://doi.org/10.1109/tgrs.2018.2833156openalex-snapshot

High-Resolution PolSAR Scene Classification With Pretrained Deep Convnets and Manifold Polarimetric Parameters

inferred← citeshttps://doi.org/10.1109/tqe.2023.3338970openalex-snapshot

Exploiting the Quantum Advantage for Satellite Image Processing: Review and Assessment

inferred← citeshttps://doi.org/10.1145/3664647.3681559openalex-snapshot

WaveDN: A Wavelet-based Training-free Zero-shot Enhancement for Vision-Language Models

inferred← citeshttps://doi.org/10.1145/3718362openalex-snapshot

Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey

inferred← citeshttps://doi.org/10.1371/journal.pone.0309997openalex-snapshot

Class-aware feature attention-based semantic segmentation on hyperspectral images

inferred← citeshttps://doi.org/10.14324/111.444/000177.v2openalex-snapshot

BoatNet: Automated Small Boat Composition Detection using Deep Learning on Satellite Imagery

inferred← citeshttps://doi.org/10.14324/111.444/ucloe.000058openalex-snapshot

BoatNet: automated small boat composition detection using deep learning on satellite imagery

inferred← citeshttps://doi.org/10.14569/ijacsa.2022.01312104openalex-snapshot

Hybrid Deep Learning Architecture for Land Use: Land Cover Images Classification with a Comparative and Experimental Study

inferred← citeshttps://doi.org/10.1609/aaai.v35i17.17728openalex-snapshot

Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing

inferred← citeshttps://doi.org/10.1609/aaai.v36i3.20230openalex-snapshot

Task-Level Self-Supervision for Cross-Domain Few-Shot Learning

inferred← citeshttps://doi.org/10.1609/aaai.v36i8.20796openalex-snapshot

Max-Margin Contrastive Learning

inferred← citeshttps://doi.org/10.1609/aaai.v37i1.25152openalex-snapshot

CALIP: Zero-Shot Enhancement of CLIP with Parameter-Free Attention

inferred← citeshttps://doi.org/10.1609/aaai.v37i1.25172openalex-snapshot

NLIP: Noise-Robust Language-Image Pre-training

inferred← citeshttps://doi.org/10.1609/aaai.v38i10.29037openalex-snapshot

Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior

inferred← citeshttps://doi.org/10.1609/aaai.v38i2.27918openalex-snapshot

Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt Tuning

inferred← citeshttps://doi.org/10.1609/aaai.v38i3.27950openalex-snapshot

LAMM: Label Alignment for Multi-Modal Prompt Learning

inferred← citeshttps://doi.org/10.1609/aaai.v38i3.27997openalex-snapshot

COMMA: Co-articulated Multi-Modal Learning

inferred← citeshttps://doi.org/10.1609/aaai.v38i3.28064openalex-snapshot

LaViP: Language-Grounded Visual Prompting

inferred← citeshttps://doi.org/10.1609/aaai.v38i5.28311openalex-snapshot

Compound Text-Guided Prompt Tuning via Image-Adaptive Cues

inferred← citeshttps://doi.org/10.1609/aaai.v38i6.28316openalex-snapshot

Data-Free Generalized Zero-Shot Learning

inferred← citeshttps://doi.org/10.1609/aaai.v38i6.28393openalex-snapshot

SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensing

inferred← citeshttps://doi.org/10.1609/aaai.v38i7.28568openalex-snapshot

Concept-Guided Prompt Learning for Generalization in Vision-Language Models

inferred← citeshttps://doi.org/10.1609/aaai.v39i1.32033openalex-snapshot

TrojanDec: Data-free Detection of Trojan Inputs in Self-supervised Learning

inferred← citeshttps://doi.org/10.1609/aaai.v39i18.34125openalex-snapshot

Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning

inferred← citeshttps://doi.org/10.1609/aaai.v39i20.35389openalex-snapshot

From Logistic Regression to the Perceptron Algorithm: Exploring Gradient Descent with Large Step Sizes

inferred← citeshttps://doi.org/10.1609/aaai.v39i21.34372openalex-snapshot

Exploring the Better Multimodal Synergy Strategy for Vision-Language Models

inferred← citeshttps://doi.org/10.1609/aaai.v39i25.34831openalex-snapshot

Interpretable Failure Detection with Human-Level Concepts

inferred← citeshttps://doi.org/10.1609/aaai.v39i9.32975openalex-snapshot

FATE: Feature-Adapted Parameter Tuning for Vision-Language Models

inferred← citeshttps://doi.org/10.17762/ijritcc.v11i10.8701openalex-snapshot

An Overview of Deep Learning Networks for Remote Sensing Applications

inferred← citeshttps://doi.org/10.17771/pucrio.acad.64761openalex-snapshot

ON MACHINE LEARNING TECHNIQUES TOWARD PATH LOSS MODELING IN 5G AND BEYOND WIRELESS SYSTEMS

inferred← citeshttps://doi.org/10.1787/dc8e85d5-enopenalex-snapshot

Monitoring land use in cities using satellite imagery and deep learning

inferred← citeshttps://doi.org/10.18174/583842openalex-snapshot

Assessing land use following tropical deforestation : Combining remote sensing and deep learning

inferred← citeshttps://doi.org/10.21203/rs.3.rs-6497131/v1openalex-snapshot

Automating image classification by using multi-resolution spaceborne imagery, cloud-based machine learning algorithms and open-source software and data

inferred← citeshttps://doi.org/10.21275/sr231218190011openalex-snapshot

Impact of Deep Learning in Analytics of Climate Change: A Survey

inferred← citeshttps://doi.org/10.2139/ssrn.5258919openalex-snapshot

Sift-as-Queries: Anchoring Transformer Attention for Aerial Scene Classification

inferred← citeshttps://doi.org/10.2139/ssrn.5363884openalex-snapshot

Analysis of Ecosystem Classification and Pattern Evolution in Shengjin Lake National Nature Reserve Based on Dsanet

inferred← citeshttps://doi.org/10.21817/indjcse/2021/v12i5/211205119openalex-snapshot

SATELLITE IMAGE CLASSIFICATION: FROM HANDCRAFTED FEATURES TO DEEP LEARNING FEATURES

inferred← citeshttps://doi.org/10.22541/essoar.171578795.50505421/v1openalex-snapshot

A Comparative Study of Transfer Learning, Convolutional Neural Network, and Random Forest for Satellite-Image-Based Land Use Classification

inferred← citeshttps://doi.org/10.31224/4629openalex-snapshot

Adversarial and Generative Deep Learning for Data Privacy in Human-Centered Artificial Intelligence

inferred← citeshttps://doi.org/10.31341/jios.45.2.5openalex-snapshot

Spectral Indexes Evaluation for Satellite Images Classification using CNN

inferred← citeshttps://doi.org/10.3233/faia230574openalex-snapshot

GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing

inferred← citeshttps://doi.org/10.3233/faia230595openalex-snapshot

Instance-Wise Adaptive Tuning and Caching for Vision-Language Models

inferred← citeshttps://doi.org/10.32620/reks.2022.1.09openalex-snapshot

Convolutional neural network hyperparameter optimization applied to land cover classification

inferred← citeshttps://doi.org/10.32657/10356/181746openalex-snapshot

Towards unbiased, accurate and robust fine-tuning of zero-shot vision models

inferred← citeshttps://doi.org/10.32734/jsi.v6i01.9229openalex-snapshot

Analysis of land cover change due to deforestation at Holiday Resort Nature Park, North Sumatra Province, Indonesia

inferred← citeshttps://doi.org/10.32985/ijeces.13.10.6openalex-snapshot

Automatic land cover classification with SAR imagery and Machine learning using Google Earth Engine

inferred← citeshttps://doi.org/10.33130/ajct.2021v07i01.033openalex-snapshot

An Overview of Different Techniques to Provide Semantics to Remote Sensing Data

inferred← citeshttps://doi.org/10.3390/s23188010openalex-snapshot

Remote Sensing Image Scene Classification in Hybrid Classical–Quantum Transferring CNN with Small Samples

inferred← citeshttps://doi.org/10.3390/su15129467openalex-snapshot

Machine Learning-Based Land Use and Land Cover Mapping Using Multi-Spectral Satellite Imagery: A Case Study in Egypt

inferred← citeshttps://doi.org/10.36227/techrxiv.20001764.v1openalex-snapshot

Influence of Spectral Bands on Satellite Image Classification using Vision Transformers

inferred← citeshttps://doi.org/10.36227/techrxiv.21493218.v1openalex-snapshot

Generating Views Using Atmospheric Correction for Contrastive Self-supervised Learning of Multi-spectral Images

inferred← citeshttps://doi.org/10.36227/techrxiv.21493218.v2openalex-snapshot

Generating Views Using Atmospheric Correction for Contrastive Self-supervised Learning of Multi-spectral Images

inferred← citeshttps://doi.org/10.36227/techrxiv.21493218.v3openalex-snapshot

Generating Views Using Atmospheric Correction for Contrastive Self-supervised Learning of Multi-spectral Images

inferred← citeshttps://doi.org/10.36227/techrxiv.21774761openalex-snapshot

Diverse Bayesian Active Learning with Simulated Annealing for Probabilistic Sampling

inferred← citeshttps://doi.org/10.36227/techrxiv.22581457openalex-snapshot

Remote Sensing Image Classification Using Transfer Learning Based Convolutional Neural Networks: An Experimental Overview

inferred← citeshttps://doi.org/10.36227/techrxiv.22581457.v1openalex-snapshot

Remote Sensing Image Classification Using Transfer Learning Based Convolutional Neural Networks: An Experimental Overview

inferred← citeshttps://doi.org/10.36227/techrxiv.22788866.v1openalex-snapshot

Few-Shot Remote Sensing Image Classification with Meta-Learning

inferred← citeshttps://doi.org/10.46253/j.mr.v2i3.a2openalex-snapshot

Enhanced Crow Search Optimization Algorithm and Hybrid NN-CNN Classifiers for Classification of Land Cover Images

inferred← citeshttps://doi.org/10.47611/jsrhs.v12i3.4695openalex-snapshot

Rice Fields as Mosquito Density Indicators for Malaria Prediction in Nigeria: An Anthropological View

inferred← citeshttps://doi.org/10.48550/arxiv.1812.11780openalex-snapshot

Weakly Supervised Active Learning with Cluster Annotation

inferred← citeshttps://doi.org/10.48550/arxiv.1907.09423openalex-snapshot

Satellite-Net: Automatic Extraction of Land Cover Indicators from Satellite Imagery by Deep Learning

inferred← citeshttps://doi.org/10.48550/arxiv.1910.14567openalex-snapshot

Conditional Denoising of Remote Sensing Imagery Using Cycle-Consistent Deep Generative Models

inferred← citeshttps://doi.org/10.5194/hess-22-5639-2018openalex-snapshot

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

inferred← citeshttps://doi.org/10.5194/isprs-annals-v-2-2021-101-2021openalex-snapshot

REMOTE SENSING IMAGE CLASSIFICATION WITH THE SEN12MS DATASET

inferred← citeshttps://doi.org/10.5194/isprs-annals-v-3-2022-705-2022openalex-snapshot

CONTRASTIVE SELF-SUPERVISED DATA FUSION FOR SATELLITE IMAGERY

inferred← citeshttps://doi.org/10.5194/isprs-archives-xliii-b3-2021-87-2021openalex-snapshot

SPATIAL RESLUTION SENSITIVITY ANALYSIS OF CLASSIFCIATION OF SENTINEL-2 IMAGES BY PRE-TRAINED DEEP MODELS FROM BIG EARTH NET DATABASE

inferred← citeshttps://doi.org/10.5194/isprs-archives-xliii-b3-2022-1399-2022openalex-snapshot

DO WE STILL NEED IMAGENET PRE-TRAINING IN REMOTE SENSING SCENE CLASSIFICATION?

inferred← citeshttps://doi.org/10.5204/thesis.eprints.238058openalex-snapshot

Multimodal data fusion of remote sensing and social media using machine learning for natural disaster detection and assessment

inferred← citeshttps://doi.org/10.52591/lxai202206246openalex-snapshot

Real-world multiclass land cover analysis and classification using a novel lightweight ConvNet

inferred← citeshttps://doi.org/10.54302/mausam.v74i2.6180openalex-snapshot

Short to medium range impact based forecasting of heavy rainfall in India

inferred← citeshttps://doi.org/10.5753/sibgrapi.est.2024.31659openalex-snapshot

Evaluation of Deep Learning Transfer Techniques for Mangrove Segmentation with Images of the Sentinel-2A

inferred← citeshttps://doi.org/10.5772/intechopen.90097openalex-snapshot

Technology, Science and Culture - A Global Vision, Volume II

inferred← citeshttps://doi.org/10.58825/jog.2023.17.1.75openalex-snapshot

Area Estimation of Mango and Coconut Crops using Machine Learning in Hesaraghatta Hobli of Bengaluru Urban District, Karnataka

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.