PatternNet: A benchmark dataset for performance evaluation of remote sensing image retrieval

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

Deep learning

LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

Distinctive Image Features from Scale-Invariant Keypoints

Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589

Going deeper with convolutions

Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298594 · Cited by 48,562

Histograms of Oriented Gradients for Human Detection

Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584

Reducing the dimensionality of data with neural networks

Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science · doi:10.1126/science.1127647 · Cited by 20,928

Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

Ojala, T., Pietikainen, M., & Maenpaa, T. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017623 · Cited by 15,398

Multitask learning for earth observation data classification with hybrid quantum network

Fan, F., Shi, Y., Guggemos, T., & Zhu, X. X. (2026) · Quantum Machine Intelligence · doi:10.1007/s42484-026-00415-3 · Cited by 2

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

Naali, F., Alipour-Fard, T., & Arefi, H. (2021) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xliii-b3-2021-87-2021 · Cited by 2

An end-to-end deep convolutional neural network for image restoration of sparse aperture imaging system in geostationary orbit

Zhao, W., Zhang, X., Wang, J., & Gu, Y. (2022) · Optoelectronic Imaging and Multimedia Technology · doi:10.1117/12.2643825 · Cited by 2

Nearest Neighbor Based Out-of-Distribution Detection in Remote Sensing Scene Classification

Dimitrić, D., Risojević, V., & Simić, M. (2023) · International Symposium INFOTEH-JAHORINA (INFOTEH) · doi:10.1109/infoteh57020.2023.10094135 · Cited by 2

Competent scene classification using feature fusion of pre-trained convolutional neural networks

Satharajupalli, T., Swamy, K. V., & Sailaja, M. (2023) · TELKOMNIKA (Telecommunication Computing Electronics and Control) · doi:10.12928/telkomnika.v21i4.24463 · Cited by 2

Multi-graph convolutional network for a remote sensing image few shot classification

Chen, J., & Xili, W. A. N. G. (2022) · National Remote Sensing Bulletin · doi:10.11834/jrs.20210522 · Cited by 2

An Efficient and Light Transformer-Based Segmentation Network for Remote Sensing Images of Landscapes

Chen, L., Chen, H., Xie, Y., He, T., Ye, J. B., & Zheng, Y. (2023) · Forests · doi:10.3390/f14112271 · Cited by 2

Hashing for Retrieving Long-Tailed Distributed Remote Sensing Images

Han, L., Paoletti, M. E., Moreno‐Álvarez, S., Haut, J. M., Vargas, R., & Plaza, A. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3360621 · Cited by 2

On the Fault Tolerance of Self-Supervised Training in Convolutional Neural Networks

Milazzo, R., Marco, V. D., Sio, C. D., Fosson, S. M., Morra, L., & Sterpone, L. (2024) · IEEE International Symposium on Design and Diagnostics of Electronic Circuits & Systems (DDECS) · doi:10.1109/ddecs60919.2024.10508923 · Cited by 2

Performance Analysis of Query-Based Image Tagging Model in CBIR

Devareddi, R. B., Srikrishna, A., & Shankar, R. S. (2024) · International Conference on Advancement in Computation & Computer Technologies (InCACCT) · doi:10.1109/incacct61598.2024.10550967 · Cited by 2

Advancements in cross-domain remote sensing scene interpretation

Zheng, X., Xiao, X., Chen, X., Lu, W., Liu, X., & Lu, X. (2024) · Journal of Image and Graphics · doi:10.11834/jig.240009 · Cited by 2

Selective Alignment Transformer for Partial-Set Remote Sensing Image Cross-Scene Classification

Li, K., Liu, Z., & Zhang, Z. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3424553 · Cited by 2

Dynamic manifold-based sample selection in contrastive learning for remote sensing image retrieval

Liu, Q., Ge, Y., Wang, S., Wang, T., & Xu, J. (2024) · The Visual Computer · doi:10.1007/s00371-024-03649-z · Cited by 3

Semantic-Enhanced Foundation Model for Coastal Land Use Recognition from Optical Satellite Images

Shao, M., Xie, X. H., Li, K., Li, C., & Zhou, X. (2024) · Applied Sciences · doi:10.3390/app14209431 · Cited by 2

Mapping landslides on Earth, Moon, and Mars using satellite imagery and deep learning techniques

Prakash, N., Bickel, V., & Manconi, A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-823868-4.00008-8 · Cited by 2

Multi-expert contrastive learning for remote sensing long-tailed image classification

Zhang, L., Peng, L., Yang, C., & Ding, X. (2024) · International Journal of Remote Sensing · doi:10.1080/01431161.2024.2433751 · Cited by 4

基于多尺度无参数注意力机制增强网络的遥感图像超分辨率重建

Jian, 郑. Z., Zilong, 刘. L., & Xiangchun, 于. Y. (2024) · Laser & Optoelectronics Progress · doi:10.3788/lop241057 · Cited by 2

AFEV-INet: adaptive feature extraction variational interactive network for remote sensing image denoising

Cheng, L., Du, W., Li, Z., & Jia, X. (2025) · Multimedia Systems · doi:10.1007/s00530-025-01680-1 · Cited by 2

Semantic Co-Occurrence and Relationship Modeling for Remote Sensing Image Segmentation

Zhang, Y., Song, H., Wang, Q., Jin, P., & Shen, T. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3540789 · Cited by 2

A method for generating obstacle sample datasets in coastal remote sensing scenes based on out-of-distribution detection

Ji, C., Cheng, T., Li, S., Gu, J., & Cheng, L. (2025) · Marine Geodesy · doi:10.1080/01490419.2025.2474481 · Cited by 2

Class Bias Correction Matters: A Class-Incremental Learning Framework for Remote Sensing Scene Classification

Wei, Y., Pan, Z., & Wu, Y. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3553141 · Cited by 2

MAGAN: multi-head attention generative adversarial network for remote sensing image classification

Li, K., Luo, Z., Shen, K., Lu, J., & Li, Z. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-04153-0 · Cited by 2

Remote Sensing Image Jitter Restoration Based on Deep Generative Adversarial Network

Zhang, Z., Zhou, Q., Xu, Y., Ma, L., & Iwasaki, A. (2021) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss47720.2021.9554491 · Cited by 2

Remote Sensing Image Retrieval Based on 3D-Local Ternary Pattern (LTP) Features and Non-subsampled Shearlet Transform (NSST) Domain Statistical Features

Baruah, H. G., Nath, V. K., & Hazarika, D. (2022) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2022.018339 · Cited by 2

Improving high-resolution satellite images retrieval using Linear SVM classifier and data augmentation

Sebai, H., & Kourgli, A. (2018) · International Conference on Pattern Analysis and Intelligent Systems (PAIS) · doi:10.1109/pais.2018.8598536 · Cited by 2

Scene Recognition with Deep Learning Methods Using Aerial Images

Sen, O., & Keleş, H. Y. (2019) · Signal Processing and Communications Applications Conference (SIU) · doi:10.1109/siu.2019.8806616 · Cited by 2

A Multilevel Mapping Strategy to Calculate the Information Content of Remotely Sensed Imagery

Fang, S., Zhou, X., & Zhang, J. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8100464 · Cited by 2

Low Resolution for DNN in SAR

Calota, I., Faur, D., & Datcu, M. P. (2020) · IEEE Radar Conference (RadarConf) · doi:10.1109/radarconf2043947.2020.9266608 · Cited by 2

Query-Adaptive Feature Fusion Base on Convolutional Neural Networks for Remote Sensing Image Retrieval

Ye, F., Chen, S., Meng, X., & Xin, J. (2021) · International Conference on Digital Society and Intelligent Systems (DSInS) · doi:10.1109/dsins54396.2021.9670607 · Cited by 2

Taking the Long View: Enhancing Learning On Multi-Temporal, High-Resolution, and Disparate Remote Sensing Data

Correa, S., Pérez, G., Jaramillo, P., & Taneja, J. (2023) · ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys) · doi:10.1145/3600100.3623722 · Cited by 2

Onthology-based Masking Loss for Improved Generalization in Remote Sensing Semantic Image Retrieval

Schumann, A., Sommer, L. W., Vogler, M., & Beyerer, J. (2018) · IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) · doi:10.1109/avss.2018.8639411 · Cited by 2

THE JOINT SPATIAL AND RADIOMETRIC TRANSFORMER FOR REMOTE SENSING IMAGE RETRIEVAL

Wang, Y., Yu, D., Ji, S., Cheng, Q., & Luo, M. (2020) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xliii-b3-2020-227-2020 · Cited by 2

Evaluation of Fuzzy Integral Data Fusion Methods for Rare Object Detection in High-Resolution Satellite Imagery

Cannaday, A. B., Davis, C. H., & Maltenfort, A. J. (2020) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata50022.2020.9377990 · Cited by 2

Zero-Shot Remote Sensing Image Super-Resolution Based on Image Continuity and Self Tessellations

Bose, R., Rangnekar, V., Banerjee, B., & Chaudhuri, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-92659-5_42 · Cited by 2

Contribution to Object Extraction in Cartography : A Novel Deep Learning-Based Solution to Recognise, Segment and Post-Process the Road Transport Network as a Continuous Geospatial Element in High-Resolution Aerial Orthoimagery

Cira, C.-I. (2022) · doi:10.20868/upm.thesis.70152 · Cited by 2

Few-Shot Remote Sensing Image Classification with Meta-LearningPreprint

Sharma, S., Roscher, R., Riedel, M., & Cavallaro, G. (2023) · doi:10.36227/techrxiv.22788866.v1 · Cited by 2

FedRS-Bench: A Realistic Federated Learning Dataset and Benchmark for Remote SensingPreprint

Zhao, H., Peng, P., Chen, C., Huang, L., & Liu, G. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6865775 · Cited by 2

ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression

Burgert, T., Stoll, O., Rota, P., & Demir, B. (2025) · arXiv · doi:10.48550/arxiv.2509.20234 · Cited by 5

Anthropogenic Object Localization: Evaluation of Broad-Area High-Resolution Imagery Scans Using Deep Learning in Overhead Imagery

Hurt, J. A., Popescu, I., Davis, C. H., & Scott, G. J. (2023) · Sensors · doi:10.3390/s23187766 · Cited by 1

Efficient geospatial mapping of buildings, woodlands, water and roads from aerial imagery using deep learning

Abbas, S., Almadhor, A. S., Sampedro, G. A., Alsubai, S., Hejaili, A. A., Strážovská, Ľ., & Zaidi, M. M. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2039 · Cited by 1

Adaptive Global-local Fusion Network Based Deep Unsupervised Hashing for Remote Sensing Image Retrieval

Xu, Z., Zhou, Y., Sheng, Q. Z., Li, C., Lou, T., & Jing, W. (2024) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme57554.2024.10687436 · Cited by 1

A novel approach for image retrieval in remote sensing using vision-language-based image caption generation

Yadav, P. S., Tyagi, D. K., & Vipparthi, S. K. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20447-w · Cited by 1

TeCCo: A Terminal-Cloud Cross-Domain Collaborative Framework for Remote Sensing Image Classification

Zhang, T., Cheng, P., Zhao, L., Wang, Z., Kong, L., Liu, C., Xu, G., & Sun, X. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3515464 · Cited by 1

Deep Model Pruning without Finetuning for Few Category Datasets

Huang, Y., Xie, J., & Wu, C. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10888517 · Cited by 1

Exploratory Study on the Impact of Data Augmentation on Aircraft Type Recognition from Remote Sensing Images

Ahmad, H. S., Talib, M. W. A., & Nasir, Q. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-1188-1_18 · Cited by 1

Feature transformation and statistical calibration for cross-domain few-shot classification

Liu, J., Deng, J., Cui, J., & Luo, W. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111181 · Cited by 1

Near-Infrared Band Synthesis From Earth Observation Imagery With Learned Location Embeddings and Task-Driven Loss Functions

Donike, S., Aybar, C., Contreras, J., & Gómez‐Chova, L. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3608941 · Cited by 1

Automatic detection of floating aquatic vegetation from remote sensing data

Soria, J. M., Soria, E., & Molner, J. V. (2025) · International Journal of Remote Sensing · doi:10.1080/01431161.2025.2561125 · Cited by 1

Low-light remote sensing image enhancement via deep Retinex network

Dai, H., Zhao, H., Jiang, Z., Li, S., Su, Y., & Fan, X. (2025) · Optoelectronic Imaging and Multimedia Technology · doi:10.1117/12.3074586 · Cited by 1

Mutual Cascade Prompting for Probability-Aligned Unsupervised Domain Adaptation in Cross-Scene Classification

Ye, Y., Wang, S., Zhao, X. T., Yu, Y., Fu, Z., & Lin, J. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3632924 · Cited by 1

Open-vocabulary object detection for high-resolution remote sensing images

Li, H. (2025) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2025.104566 · Cited by 3

Knowledge Distillation Meets Reinforcement Learning: A Cluster-Driven Approach to Image Processing

Kitrungrotsakul, T., Xu, Y., & Srichola, P. (2025) · Sensors · doi:10.3390/s26010209 · Cited by 1

AGPL-KEM : Attribute-guided prompt learning with knowledge experts mixture for few-shot remote sensing image classification

Wu, C., Zhu, C., Xu, Q., Liu, X., Zhang, Y., Wang, L., & Wu, J. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115375 · Cited by 1

COOkeD: Ensemble-Based OOD Detection in the Era of Zero-Shot CLIP

Humblot-Renaux, G., Franchi, G., Escalera, S., & Moeslund, T. B. (2025) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw69036.2025.00033 · Cited by 1

OATS-RS: Ontology-Aware Adaptive and Selective Zero-Shot Scene Classification for Remote Sensing

Horváth, J. (2026) · Remote Sensing · doi:10.3390/rs18122038 · Cited by 1

Deep Instance Search Network for Remote Sensing Image Retrieval

Wang, H., Zhou, Z., & Bo, D. (2020) · Chinese Control Conference (CCC) · doi:10.23919/ccc50068.2020.9189512 · Cited by 1

A Lightweight Model for Remote Sensing Image Retrieval with Knowledge Distillation and Mining Interclass Characteristics

Quan, K.-A. C., Nguyen, V.-T., & Tran, M. (2021) · NAFOSTED Conference on Information and Computer Science (NICS) · doi:10.1109/nics54270.2021.9701545 · Cited by 1

INTERLINKED FEATURE QUERYBASED IMAGE RETRIEVAL MODEL FOR CONTENT-BASED IMAGE RETRIEVAL

Devareddi, R. B., & Srikrishna, A. (2022) · Indian Journal of Computer Science and Engineering · doi:10.21817/indjcse/2022/v13i5/221305013 · Cited by 1

Computer Vision for International Border Legibility

Ortega, T., Nelson, T., Crane, S., Myers-Dean, J., & Wehrwein, S. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00383 · Cited by 1

Attention-based Residual Network for Single Image Remote Sensing Super-resolution

Barman, T., & Deka, B. (2022) · International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · doi:10.1109/icccis56430.2022.10037720 · Cited by 1

Silhouette vanished contour discovery of aerial view images by exploiting pixel divergence

Devareddi, R. B., & Srikrishna, A. (2023) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v12.i3.pp1312-1322 · Cited by 1

ViGEO: an Assessment of Vision GNNs in Earth Observation

Colomba, L., & Garza, P. (2023) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw60847.2023.00110 · Cited by 1

Investigations on Deep Learning Pre-trained Model VGG-19 Using Transfer Learning for Remote Sensing Image Classification on Benchmark Datasets

Gupta, N., Singh, J., Singh, S., Joshi, G., & Mittal, A. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-99-8476-3_11 · Cited by 1

Investigations on Deep Learning Pre-trained Model Inception-V3 Using Transfer Learning for Remote Sensing Image Classification on Benchmark Datasets

Gupta, N., Singh, S., Singh, J., Mittal, A., & Joshi, G. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-99-9040-5_16 · Cited by 1

DiffuPrompter: Pixel-Level Automatic Annotation for High-Resolution Remote Sensing Images with Foundation Models

Li, H., Wei, Y. J., Peng, H., & Zhang, W. (2024) · Remote Sensing · doi:10.3390/rs16112004 · Cited by 1

Manifold Constraint Regularization for Remote Sensing Image Generation

Su, X., Zheng, C., Qiang, W., Wu, F., Zhao, J., Sun, F., & Xiong, H. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3441631 · Cited by 1

Domain Adaptation for Performance Enhancement of Deep Learning Models for Remote Sensing Scenes Classification

Lasloum, T., Youssef, B. B., & Alhichri, H. S. (2024) · Advances in systems analysis, software engineering, and high performance computing book series · doi:10.4018/978-1-6684-3795-7.ch003 · Cited by 1

A Classification Method for Satellite Imagery Utilizing Transfer Learning Techniques

Gover, J., & Sharma, M. (2025) · International Conference on Signal Processing, Computing and Control (ISPCC) · doi:10.1109/ispcc66872.2025.11039373 · Cited by 1

A conflict-aware learning network in generative models for enhancing retrieval efficiency of remote sensing images

Unar, S., Nazar, M., Kumbhar, F. H., Khokhar, S.-U.-D., Kulevome, D. K. B., & Elkhalil, A. (2025) · Cluster Computing · doi:10.1007/s10586-025-05599-0 · Cited by 1

Hqsan: a hybrid quantum self-attention network for remote sensing image scene classification

Wang, R., Zhang, Z., Shen, Y., Sui, Z., & Lin, K. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07922-3 · Cited by 2

Machine Unlearning for Source-Free Unsupervised Partial-Domain Adaptation in Remote Sensing

Yang, J., Li, P., Yun, X., Zhong, X., & Wu, D. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3637240 · Cited by 1

A novel rotation invariance hashing network for fast remote sensing image retrieval

Zou, C., Wan, S., Jin, P., & Li, X. (2018) · International Conference on Digital Image Processing · doi:10.1117/12.2503185 · Cited by 1

STCEC: A Remote Sensing Dataset for Identifying Spatial-Temporal Change in Homogeneous and Heterogeneous Environments

Ali, T. F., & Woodley, A. (2019) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta47822.2019.8946005 · Cited by 1

Incorporating Human Views into Unsupervised Deep Transfer Learning for Remote Sensing Image Retrieval

Liu, Y., Chen, C., Han, Z., Liu, Y., & Ding, L. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59830-3_34 · Cited by 1

UJN-Traffic: A Benchmark Dataset for Performance Evaluation of Traffic Element Classification

Li, Y., Han, S., Shen, Y., Liu, Z., Dong, J., & Xu, T. (2021) · Communications in computer and information science · doi:10.1007/978-981-16-7213-2_18 · Cited by 1

Improving Image Clustering through Sample Ranking and Its Application to Remote Sensing Images

Li, Q., & Qiu, G. (2022) · Remote Sensing · doi:10.3390/rs14143317 · Cited by 2

Unifying Remote Sensing Image Retrieval and Classification with Robust Fine-tuningPreprint

Gominski, D., Gouet-Brunet, V., & Chen, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.13392 · Cited by 1

Deep Transfer Learning for Land Use Land Cover Classification: A Comparative StudyPreprint

Naushad, R., & Kaur, T. (2021) · arXiv (Cornell University) · Cited by 1

Sentinel2GlobalLULC: A deep-learning-ready Sentinel-2 RGB image dataset for global land use/cover mappingPreprint

Benhammou, Y., Alcaraz‐Segura, D., Guirado, E., Khaldi, R., Achchab, B., Herrera, F., & Tabik, S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.12.01.470768 · Cited by 1

Image feature representation using deep learning for instance search and scene recognition = Representación de características de la imagen utilizando el aprendizaje profundo para la búsqueda de instancias y el reconocimiento de escenas

Saikia, S. (2021) · doi:10.18002/10612/15059 · Cited by 1

Open-Vocabulary Object Detection for Remote Sensing ImagesPreprint

Li, H. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5393893 · Cited by 1

A Study on the Sensitivity-Based Discriminative Hyperspectral Image Content Representation

Ahmed, O. B., Urruty, T., Richard, N., & Fernández-Maloigne, C. (2018) · International Workshop on Content-Based Multimedia Indexing (CBMI) · doi:10.1109/cbmi.2018.8516560

Procedural Learning With Robust Visual Features via Low Rank Prior

Li, H., Chen, L., Ding, H., Li, Q., Sun, B., & Wu, G. (2019) · IEEE Access · doi:10.1109/access.2019.2894841

V-RSIR: A WEB-BASED TOOL AND BENCHMARK DATASET FOR REMOTE SENSING IMAGE RETRIEVAL

Hou, D., & Xing, H. (2019) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xlii-2-w13-1545-2019

Remote Sensing Satellite Jitter Detection Based on Image Registration and Convolutional Neural Network Fusion

Zhang, Z., Iwasaki, A., & Xu, G. (2019) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2019.8899150

A novel hybrid method for synthesising missing pixels in remote sensing imagery

Ali, T. F. (2020) · Queensland University of Technology · doi:10.5204/thesis.eprints.205280

Evaluation of Datasets for CNN based Image Classification

Marbhal, S., & Kumar, M. (2020)

Remote Sensing Image Classification Based On Densely Connected Convolutional Networks

Gao, Y., & Wu, M. (2021) · IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) · doi:10.1109/icspcc52875.2021.9564766

Remote Sensing Image Retrieval Based on Key Region Detection

Ye, F., Zhang, R., Xing, Y., Xin, J., & Li, D. (2022) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2216/1/012110

Derin Öğrenme Yaklaşımlarıyla Çevresel İzlemeye Yönelik Çok-Sınıflı Sınıflandırma

Atik, Ş. Ö. (2022) · European Journal of Science and Technology · doi:10.31590/ejosat.1057643

Few-Shot Remote Sensing Image Classification with Meta-LearningPreprint

Sharma, S., Roscher, R., Riedel, M., & Cavallaro, G. (2023) · doi:10.36227/techrxiv.22788866

Sar-Cdl: Sar Image Interpretable Despeckling Through Convolutional Dictionary Learning NetworkPreprint

Zhao, X., Ren, F., Sun, H., Zhang, Y., Ma, Y., & Qi, Q. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4493650

Attention-based localized hash retrieval for large-scale remote sensing images using deep feature splitting strategy

Sudha, S. K., & Aji, S. (2023) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.17.032404

Metric networks for enhanced perception of non-local semantic information

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