Deep learning for Amazon satellite image analysis

Adam: A Method for Stochastic Optimization

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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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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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

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Xception: Deep Learning with Depthwise Separable Convolutions

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Learning multi-label scene classification

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Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation

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DenseNet: Implementing Efficient ConvNet Descriptor PyramidsPreprint

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DATA AUGMENTATION AND DYNAMIC LINEAR MODELS

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Xception: Deep Learning with Depthwise Separable Convolutions

Chollet, F. (2016) · arXiv · doi:10.48550/arxiv.1610.02357 · Cited by 538 · see citing works

Object Detection Networks on Convolutional Feature Maps

Ren, S., He, K., Girshick, R., Zhang, X., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2601099 · Cited by 454 · see citing works

A weighted voting framework for classifiers ensembles

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Autonomous ships on the high seas

Levander, O. (2017) · IEEE Spectrum · doi:10.1109/mspec.2017.7833502 · Cited by 108 · see citing works

Sensitivity of Barnes Ice Cap, Baffin Island, Canada, to climate state and internal dynamics

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Satellite alerts track deforestation in real time

Popkin, G. (2016) · Nature · doi:10.1038/530392a · Cited by 21 · see citing works

SAR and InSAR for flood monitoring: Examples with COSMO/SkyMed data

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Remote Sensing of Natural Disasters [Scanning the Issue]

Chen, K., Serpico, S. B., & Smith, J. A. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2205835 · Cited by 8 · see citing works

Monitoring Rainforest Dynamics in the Amazon with MODIS Land Products

HUETE, A. R., Running, S. W., & Myneni, R. B. (2006) · doi:10.1109/igarss.2006.72 · Cited by 7 · see citing works

Remote Sensing of Natural Disasters

Chien, S., & Tanpipat, V. (2012) · Springer eBooks · doi:10.1007/978-1-4614-5684-1_17 · Cited by 6 · see citing works

Residual Network with Delayed Max Pooling for Very Large Scale Plant Identification.

Hang, S. T., & Aono, M. (2017) · CLEF (Working Notes) · Cited by 4 · see citing works

Using satellites to predict earthquakes, volcano eruptions, identify and track tsunamis from space

Losik, L. (2012) · Proceedings - IEEE Aerospace Conference · doi:10.1109/aero.2012.6187030 · Cited by 2 · see citing works

Tackling climate change with machine learning

Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works

Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities

Persello, C., Wegner, J. D., Hänsch, R., Tuia, D., Ghamisi, P., Koeva, M., & Camps‐Valls, G. (2022) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2021.3136100 · Cited by 197 · see citing works

Fire Detection Method in Smart City Environments Using a Deep-Learning-Based Approach

Avazov, K., Mukhiddinov, M., Makhmudov, F., & Cho, Y. I. (2021) · Electronics · doi:10.3390/electronics11010073 · Cited by 142 · see citing works

Wildfire Segmentation Using Deep Vision Transformers

Ghali, R., Akhloufi, M. A., Jmal, M., Mseddi, W. S., & Attia, R. (2021) · Remote Sensing · doi:10.3390/rs13173527 · Cited by 91 · see citing works

Classification of Landscape Affected by Deforestation Using High-Resolution Remote Sensing Data and Deep-Learning Techniques

Lee, S.-H., Han, K., Lee, K., Lee, K., Oh, K.-Y., & Lee, M.-J. (2020) · Remote Sensing · doi:10.3390/rs12203372 · Cited by 87 · see citing works

Security Approaches in Machine Learning for Satellite Communication

Rath, M., & Mishra, S. (2019) · Studies in computational intelligence · doi:10.1007/978-3-030-20212-5_10 · Cited by 43 · see citing works

Deep AlexNet with Reduced Number of Trainable Parameters for Satellite Image Classification

Unnikrishnan, A., Sowmya, V., & Soman, K. P. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.10.342 · Cited by 37 · see citing works

Learning CNN Filters From User-Drawn Image Markers for Coconut-Tree Image Classification

de Souza, I. E., & Falcão, A. X. (2020) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2020.3020098 · Cited by 31 · see citing works

Forest Cover Change Detection Using Satellite Images

Kalwar, A., Mathur, R., Chavan, S., & Narvekar, C. (2021) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-16-3961-6_46 · Cited by 6 · see citing works

Towards Real-Time Illegal Logging Monitoring: Gas-Powered Chainsaw Logging Detection System using K-Nearest Neighbors

Arevalo, J. D. C., Calica, P. C., Celestino, B. A. D. R., Dimapunong, K. A., Lopez, D. J. D., & Austria, Y. D. (2020) · IEEE International Conference on System Engineering and Technology (ICSET) · doi:10.1109/icset51301.2020.9265375 · Cited by 5 · see citing works

Deep Learning on High Spatial and Temporal Cadence Satellite Imagery for Field Boundary Delineation

Shah, S. R. A., Rehman, O. U., Ishaq, R. A. F., Shabbir, Y., & Ahmad, I. (2021) · International Conference on Aerospace Science and Engineering (ICASE) · doi:10.1109/icase54940.2021.9904133 · Cited by 3 · see citing works

Classification of Low-Resolution Satellite Images Using Fractal Augmented Descriptors

Padhy, R., Swain, S. S., Dash, S. K., & Mishra, J. (2021) · International Journal of Image and Graphics · doi:10.1142/s0219467822500024 · Cited by 3 · see citing works

Remote Monitoring Systems for Conservation of the Amazon Rainforest: A Systematic Review

Cepeda, J. A. T., Ospina-Mendivelso, N., Díaz-Palacios, V. M., Nava, D. P. C., Triana, A., Cano, C. C., Corredor, D. A., & Varón, M. (2025) · Mundo Amazónico · doi:10.15446/ma.v16n1.114004 · Cited by 1 · see citing works

Landform Segmentation in Terrain Images Using Image Translation Neural Network Architectures

Bajaj, A., Bhardwaj, A., Tuteja, Y., & Abraham, A. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-64850-2_47 · Cited by 1 · see citing works

Estudio comparativo de técnicas de visión artificial y procesamiento de imágenes enfocadas a la detección de cambios en coberturas boscosas

Revelo, M., & Yolanda, M. (2020)

Annotating Satellite Images of Forests with Keywords from a Specialized Corpus in the Context of Change Detection

Neptune, N., & Mothe, J. (2023) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.11073078

Real time deforestation detection using ANN and Satellite images

Kehl, T. N., Todt, V., Veronez, M. R., & Cazella, S. C. (2015) · SpringerBriefs in computer science · doi:10.1007/978-3-319-15741-2 · Cited by 1 · see citing works

Multi-Label Classification on Remote-Sensing ImagesPreprint

SINGH, A. K., & Shankar, B. U. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2201.01971

Evaluation of Deep Learning Techniques for Deforestation Detection in the Brazilian Amazon and Cerrado Biomes From Remote Sensing Imagery

Ortega, M. X., Feitosa, R. Q., Happ, P. N., Almeida, C. A., & Gomes, A. R. (2020) · Remote Sensing · doi:10.3390/rs12060910 · Cited by 102 · see citing works

Identifying Land Patterns from Satellite Imagery in Amazon Rainforest using Deep LearningPreprint

Rakshit, S., Debnath, S., & Mondal, D. R. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.00340 · Cited by 8 · see citing works