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

Deep Residual Learning for Image Recognition

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ImageNet classification with deep convolutional neural networks

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Going deeper with convolutions

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ImageNet Large Scale Visual Recognition Challenge

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Rethinking the Inception Architecture for Computer Vision

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A Practical Guide to Splines

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Backpropagation Applied to Handwritten Zip Code Recognition

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Identity mappings in deep residual networks

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

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ELSET: Design of an Ensemble Deep Learning Model for improving satellite image Classification Efficiency via Temporal Analysis

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Super-resolution of Sentinel-2 images using Wasserstein GAN

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Task-Oriented Multi-Modal Mutual Learning for Vision-Language Models

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A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning

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Satellite Imagery Classification with Deep Learning : A Survey

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Tracking Socio-Economic Development in Rural India over Two Decades Using Satellite Imagery

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Have Foundational Models Seen Satellite Images?

Panigrahi, A., Verma, S., Terris, M., & Vakalopoulou, M. (2023) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss52108.2023.10283274 · Cited by 5

Influence of Spectral Bands on Satellite Image Classification using Vision TransformersPreprint

Anil, A., Variyar, V. V. S., Sowmya, V., Sukumar, A., Krichen, M., & Vinayakumar, R. (2022) · doi:10.36227/techrxiv.20001764 · Cited by 5

Faster Parameter-Efficient Tuning with Token Redundancy Reduction

Kim, K., Park, J., Kim, J., Kwon, H., & Sohn, K. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52734.2025.02810 · Cited by 5

Adaptive Parameter Selection for Tuning Vision-Language Models

Zhang, Y., Deng, Y., Guo, M.-H., & Hu, S. (2025) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52734.2025.00404 · Cited by 4

FedSECA: Sign Election and Coordinate-Wise Aggregation of Gradients for Byzantine Tolerant Federated Learning

Benjamin, J. G., Asokan, M., Yaqub, M. K., & Nandakumar, K. (2025) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw67362.2025.00165 · Cited by 4

Integrating Convolutional, Transformer, and Graph Neural Networks for Precision Agriculture and Food Security

Mahareek, E. A., Çifçi, M. A., & Desuky, A. S. (2025) · AgriEngineering · doi:10.3390/agriengineering7100353 · Cited by 4

Semi-supervised few-shot learning via ensemble-based adaptive clustering-aware pseudo-labeling

Al‐Habib, M. I., Zhang, Z., Noman, A., Al-Qatf, M., & Abdelaziz, M. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.114225 · Cited by 4

Zero-shot domain adaptation for remote sensing image classification with vision-language models

Wang, Z., Pei, C., Ma, X., & Pun, M.-O. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132470 · Cited by 4

Doppler-Adaptive Digital Semantic Communication for Low Earth Orbit Satellite Systems

Seon, J., Lee, S., Kim, S. H., Sun, Y. G., Seo, H., Kim, D. I., & Kim, J. Y. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3614234 · Cited by 5

TriMem: Trifold Memory Framework for Continual Learning of VLMs in Remote Sensing

Guo, W., Cui, J., Cui, X., Li, J., Zhang, Z., Shao, R., Guo, M., & Li, H. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3622029 · Cited by 9

Land-Use Classification of High-Resolution Remote Sensing Imagery Incorporating Global–Local Interactive Features Across Optical Domain and Land Cover Primitives

Zhang, B., Wen, D., Lü, Y., Tian, Y., & Huang, X. (2026) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2026.3669385 · Cited by 4

Test-Time Retrieval-Augmented Adaptation for Vision-Language Models

Fan, X., Chen, X. Y., Yang, L., Yap, C. H., Qureshi, R., Dou, Q., Yap, M. H., & Shah, M. A. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.00824 · Cited by 4

Domaindiff: Boost out-of-Distribution Generalization with Synthetic Data

Miao, Q., Yuan, J., Zhang, S., Wu, F. Q., & Kuang, K. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10446788 · Cited by 4

Human Communication-Inspired Semantic–View Collaborative Network for Multispectral Remote Sensing Image Retrieval

Wu, N., Jin, W., & Fu, R. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3409417 · Cited by 4

Efficient Lossy Satellite Image Compression Using Hybrid Autoencoder Model

Badr, M. A., Elrewainy, A., & Elshafey, M. A. (2024) · doi:10.1109/iceeng58856.2024.10566288 · Cited by 4

Bayesian Exploration of Pre-Trained Models for Low-Shot Image Classification

Miao, Y., Yu, L., Zhou, F., & Deng, Z. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02251 · Cited by 4

PromptSync: Bridging Domain Gaps in Vision-Language Models through Class-Aware Prototype Alignment and Discrimination

Khandelwal, A. (2024) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00778 · Cited by 4

Instance-Level Scaling and Dynamic Margin-Alignment Knowledge Distillation for Remote Sensing Image Scene Classification

Li, C., Teng, X., Ding, Y., & Lan, L. (2024) · Remote Sensing · doi:10.3390/rs16203853 · Cited by 4

Machine Learning Model Specification for Cataloging Spatio-Temporal Models (Demo Paper)

Charette-Migneault, F., Avery, R., Pondi, B., Omojola, J., Vaccari, S., Membari, P., Peressutti, D., Yu, J., & Sundwall, J. (2024) · ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data (GeoSearch) · doi:10.1145/3681769.3698586 · Cited by 4

Dynamic Model Merging With Mixture of Weights

Ye, H., Huang, C., Shen, M., Chen, T., Huang, Y., & Ouyang, W. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3544680 · Cited by 6

Integrating Deep and Handcrafted Features for Enhanced Remote Sensing Image Classification

Abdulmajeed, V., Jouini, K., Tuama, A., & Korbaa, O. (2024) · IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) · doi:10.1109/aiccsa63423.2024.10912637 · Cited by 4

Optimization Algorithms Based on Double-Integral Coevolutionary Neurodynamics in Deep Learning

Su, D., Han, J., Yang, C., & Gui, W. (2025) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2025.125210 · Cited by 4

DBA-RMCL: Refined Metric Contrastive Learning With Dual-Branch Attention for Few-Shot Remote Sensing Image Scene Classification

Dong, R., Xia, J., Jiao, L., Zhao, J. K., Hong, L., & Yun, Z. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3564591 · Cited by 4

Sharing Task-Relevant Information in Visual Prompt Tuning by Cross-Layer Dynamic Connection

Zhou, N., Chen, J., & Huang, D. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3587587 · Cited by 8

MoE-Adapters++: Toward More Efficient Continual Learning of Vision-Language Models Via Dynamic Mixture-of-Experts Adapters

Yu, J., Huang, Z., Zhuge, Y., Zhang, L., Hu, P., Wang, D., Lu, H., & He, Y. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3597942 · Cited by 5

Hierarchical Knowledge Distillation for Efficient Model Compression and Transfer: A Multi-Level Aggregation Approach

Kitrungrotsakul, T., & Srichola, P. (2026) · Information · doi:10.3390/info17010070 · Cited by 4

A Genealogy of Foundation Models in Remote Sensing

Lane, K., & Karimzadeh, M. (2026) · ACM Transactions on Spatial Algorithms and Systems · doi:10.1145/3789505 · Cited by 7

A survey on design choices for self-supervised learning in computer vision

Wittscher, L. (2026) · Artificial Intelligence Review · doi:10.1007/s10462-026-11506-9 · Cited by 4

On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations

Wang, Z. (2026) · Algorithms · doi:10.3390/a19040318 · Cited by 4

Causal Disentanglement and Cross-Modal Alignment for Enhanced Few-Shot Learning

Jiang, T., Zhang, Z., Liu, Y., & Shi, J. Q. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.00091 · Cited by 4

Application of Massive Parallel Deep Learning Algorithm in the Prediction of Colorectal Carcinogenesis of Familial Polyposis

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Remote Sensing Mapping of Build-Up Land with Noisy Label via Fault-Tolerant Learning

Xu, G., Fang, Y., Deng, M., Sun, G., & Chen, J. (2022) · Remote Sensing · doi:10.3390/rs14092263 · Cited by 4

Classification of Agriculture Crops Using Transfer Learning

Goel, S., Markanday, S., & Mohanty, S. (2022) · OITS International Conference on Information Technology (OCIT) · doi:10.1109/ocit56763.2022.00058 · Cited by 4

Patch based Classification using ResNet for Land Cover changes detection of Batu City

Fahmi, H. (2022) · Matics Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) · doi:10.18860/mat.v14i2.20946 · Cited by 4

Visual privacy behaviour recognition for social robots based on an improved generative adversarial network

Yang, G., Lin, J., Su, Z., & Li, Y. (2023) · IET Computer Vision · doi:10.1049/cvi2.12231 · Cited by 4

Texture Based LULC Classification of Images Using QSVM

Pai, A. G., Buddhiraju, K. M., & Durbha, S. S. (2023) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss52108.2023.10283087 · Cited by 4

Development of Trustable Deep Learning Model in Remote Sensing through Explainable-AI Method Selection

Tasneem, S., & Islam, K. A. (2023) · IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) · doi:10.1109/uemcon59035.2023.10316012 · Cited by 4

Land Cover Classification in the Antioquia Region of the Tropical Andes Using NICFI Satellite Data Program Imagery and Semantic Segmentation Techniques

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Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey

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Consistent land use and land cover classification across 20 years of various high-resolution images for detecting soil sealing in Murcia, Spain

Illán-Fernández, E. J., Dirk Tiede, A., & Sudmanns, M. (2024) · Remote Sensing Applications Society and Environment · doi:10.1016/j.rsase.2024.101223 · Cited by 4

Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model

Shi, J.-X., Zhang, C., Wei, T., & Li, Y.-F. (2024) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3637528.3671945 · Cited by 4

VTPL: Visual and text prompt learning for visual-language models

Sun, B., Wu, Z., Zhang, H., & He, J. (2024) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2024.104280 · Cited by 5

Evaluation of Quantized CNN Architectures for Land Use Classification for Onboard Cube Satellite Computing

Akeboshi, W. W. N., Billones, R. K. C., Coching, J. K., Pe, A. J. L., Yeung, S. G. D., Ai, R. J. T., Sybingco, E., Dadios, E. P., & Purio, M. A. C. (2024) · International Conference on Mechatronics Engineering (ICOM) · doi:10.1109/icom61675.2024.10652460 · Cited by 4

Design of Neural Network based Approaches for Land Usage Land Cover Classification

Vijay Krishnan, M. R., Mehra, R., & Kunadharaju, H. P. R. (2024) · International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT) · doi:10.1109/iceeict61591.2024.10718442 · Cited by 4

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

Li, J., Yang, M., Tian, Y., Zhang, L., Lu, Y., Liu, J., & Wang, W. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681559 · Cited by 5

Adaptive Multi-Modality Prompt Learning

Wu, Z., Liu, Y., Zhan, M., Hu, P., & Zhu, X. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681485 · Cited by 5

Exploring the potentialities and challenges of deep learning for simulation and prediction of urban sprawl features

Belinga, A. G., Tekouabou, S. C. K., & Haziti, M. E. (2025) · Data & Policy · doi:10.1017/dap.2024.87 · Cited by 4

Machine learning and deep learning for cancer diagnosis

Soewu, T., Kaur, H., Sandhu, R., Soni, A., Ghai, D., Dhir, K., & Tripathi, S. L. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-21505-6.00009-8 · Cited by 4

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification

Zou, G., Yao, L., Liu, F., Zhang, C., Li, X., Chen, N., Xu, S., & Zhou, J. W. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10890085 · Cited by 4

Supervised desertification classification using Siamese Variational Autoencoder

Chouikhi, F., Abbes, A. B., & Farah, I. R. (2025) · International Journal of Image and Data Fusion · doi:10.1080/19479832.2025.2476544 · Cited by 4

Drop inherent biases: Multi-level attention calibration for robust cross-domain few-shot classification

Li, M., Jiang, J. B., & Yao, H. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130056 · Cited by 4

Tailoring adversarial attacks on deep neural networks for targeted class manipulation using DeepFool algorithm

Labib, S. M. F. R., Mondal, J. J., Manab, M. A., Xiao, X., & Newaz, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-87405-w · Cited by 7

Stabilizing Modality Gap & Lowering Gradient Norms Improve Zero-Shot Adversarial Robustness of VLMs

Dong, J., Koniusz, P., Qu, X., & Ong, Y.-S. (2025) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3690624.3709296 · Cited by 6

Diffusion-Enhanced Test-Time Adaptation with Text and Image Augmentation

Feng, C.-M., He, Y., Zou, J., Khan, S., Xiong, H., Li, Z., Zuo, W., Goh, R. S. M., & Liu, Y. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-025-02412-8 · Cited by 7

Enhancing Vision-Language Few-Shot Adaptation with Negative Learning

Zhang, C., Stepputtis, S., Sycara, K. P., & Xie, Y. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00576 · Cited by 10

Semantic Knowledge Distillation for Onboard Satellite Earth Observation Image Classification

Le, T.-D., Ha, V. N., Nguyen, T. T., Eappen, G., Thiruvasagam, P., Chou, H.-F., Tran, D., Garcés-Socarrás, L. M., Ríos, J. L. G., Duncán, J. C. M., et al. (2025) · IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN) · doi:10.1109/icmlcn64995.2025.11140497 · Cited by 4

Towards Efficient Benchmarking of Foundation Models in Remote Sensing: A Capabilities Encoding Approach

Adorni, P., Pham, M., May, S., & Lefèvre, S. (2025) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw67362.2025.00292 · Cited by 4

Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models

Tang, A., Shen, L., Luo, Y., Xie, S., Hu, H., Zhang, L., Du, B., & Tao, D. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3612480 · Cited by 14

Task Arithmetic in Trust Region: A Training-Free Model Merging Approach to Navigate Knowledge Conflicts

Sun, W., Li, Q., Wang, W., Geng, Y.-A., & Li, B. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3755789 · Cited by 4

Group-guided prompt learning for vision-language models

Zheng, Y., Wang, S., & Gao, Y. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129846 · Cited by 4

Fully convolutional neural nets in-the-wild

Simms, D. M. (2020) · Remote Sensing Letters · doi:10.1080/2150704x.2020.1821120 · Cited by 4

Aerial Cross-platform Path Planning Dataset

Shahid, M., & Channappayya, S. S. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00440 · Cited by 4

RSI-Mix: Data Augmentation Method for Remote Sensing Image Classification

Lu, X., Zhang, C., Ye, Q., Wang, C., Yang, C., & Wang, Q. (2022) · International Conference on Intelligent Computing and Signal Processing (ICSP) · doi:10.1109/icsp54964.2022.9778421 · Cited by 4

An Exploration into the Benefits of the CLIP model for Lifelog Retrieval

Tran, L.-D., Alam, N., Graham, Y., Vo, L. K., Diep, N. T., Nguyen, B. T., Zhou, L., & Gurrin, C. G. (2022) · International Workshop on Content-Based Multimedia Indexing (CBMI) · doi:10.1145/3549555.3549593 · Cited by 5

Using Deep Learning Approach for Land-Use and Land-Cover Classification based on Satellite images

Agarwal, R., Goel, S., & Nijhawan, R. (2022) · Asian Conference on Innovation in Technology (ASIANCON) · doi:10.1109/asiancon55314.2022.9909395 · Cited by 4

GeoTorch

Chowdhury, K., & Sarwat, M. (2022) · ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL GIS) · doi:10.1145/3557915.3561036 · Cited by 4

Deep Learning Based Patch-Wise Land Cover Land Use Classification: A New Small Benchmark Sentinel-2 Image Dataset

Alp, G., & Sertel, E. (2022) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss46834.2022.9883715 · Cited by 4

Deep learning for photovoltaic panels segmentation

Bouzaachane, K., Darouichi, A., & Guarmah, E. M. E. (2023) · Mathematical Modeling and Computing · doi:10.23939/mmc2023.03.638 · Cited by 4

XtremeCLIP: Extremely Parameter-efficient Tuning for Low-resource Vision Language Understanding

Tang, M., Wang, C., Wang, J., Tan, C., Huang, S., Chen, C., & Qian, W. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.397 · Cited by 5

Vegetation Land Segmentation with Multi-Modal and Multi-Temporal Remote Sensing Images: A Temporal Learning Approach and a New Dataset

Qu, F., Sun, Y., Zhou, M., Liu, L., Yang, H., Zhang, J., Huang, H., & Hong, D. (2023) · Remote Sensing · doi:10.3390/rs16010003 · Cited by 4

Improving DeepLabV3+ Using Normalized Satellite Indices in Land-Cover Segmentation

Herlawati, H., Abdurachman, E., Heryadi, Y., & Soeparno, H. (2023) · International Journal of Fuzzy Logic and Intelligent Systems · doi:10.5391/ijfis.2023.23.4.389 · Cited by 4

Identifying Land features from satellite images using deep learning

Nagaraju, K. A., & Chaurasia, K. (2023) · International Conference on Developments in eSystems Engineering (DeSE) · doi:10.1109/dese60595.2023.10469505 · Cited by 4

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

Cho, Y., Bae, H., Shin, S., Youn, Y. D., Joo, W., & Moon, I. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i10.29037 · Cited by 6

A novel approach for Hyper Spectral Images using Transfer Learning

Bharti, R., Saini, D., & Malik, R. (2021) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/1022/1/012120 · Cited by 4

Comparing CNN Architectures for Land Cover Classification on Multispectral Images

Engelbrecht, B., & van Zyl, T. L. (2021) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss47720.2021.9553337 · Cited by 4

Requirement-driven remote sensing metadata planning and online acquisition method for large-scale heterogeneous data

Wang, S., Li, G., Yu, W., & Ma, Y. (2021) · Geo-spatial Information Science · doi:10.1080/10095020.2021.1994358 · Cited by 4

Automatic extraction of land cover statistics from satellite imagery by deep learning

Bernasconi, E., Fausti, F. D., Pugliese, F., Scannapieco, M., & Zardetto, D. (2021) · Statistical Journal of the IAOS · doi:10.3233/sji-190555 · Cited by 4

AmazonCRIME: un conjunto de datos y punto de referencia de Inteligencia Artificial Geoespacial para la clasificación de áreas potenciales vinculadas a Crímenes Ambientales Transnacionales en la Selva Amazónica

Hidalgo, J. J. P., & Silva-Centeno, J. A. (2022) · Revista de teledetección: Revista de la Asociación Española de Teledetección · doi:10.4995/raet.2022.15710 · Cited by 4

Comparison of Various Deep CNN Models for Land Use and Land Cover Classification

Mahamunkar, G. S., & Netak, L. D. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-98404-5_46 · Cited by 4

Efficient Transfer Learning for Visual Tasks via Continuous Optimization of Prompts

Conder, J., Jefferson, J., Pages, N., Jawed, K., Nejati, A., & Sagar, M. A. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-06427-2_25 · Cited by 4

FLAMINGO: Adaptive and Resilient Federated Meta-Learning against Adversarial Attacks

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