Satellite Image Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

8 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

17 shown of 17 papers with code (33 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• SpinalNet: Deep Neural Network with Gradual Input
  7 Jul 2020 3 repositories listed
  Traditional learning with ImageNet pre-trained initial weights and SpinalNet classification layers provided the SOTA performance on STL-10, Fruits 360, Bird225, and Caltech-101 datasets.
• Reduction of Class Activation Uncertainty with Background Information
  5 May 2023 2 repositories listed
  Through the class activation mappings (CAMs) of the trained models, we observed the tendency towards looking at a bigger picture with the proposed model training methodology.
• Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification
  14 Jul 2022 2 repositories listed
  We present AiTLAS: Benchmark Arena -- an open-source benchmark suite for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO).
• Discriminative Learning of Deep Convolutional Feature Point Descriptors
  1 Dec 2015 2 repositories listed
  Deep learning has revolutionalized image-level tasks such as classification, but patch-level tasks, such as correspondence, still rely on hand-crafted features, e.
• Practical insights on the effect of different encodings, ansätze and measurements in quantum and hybrid convolutional neural networks
  25 Jun 2025 1 repository listed
  This study investigates the design choices of parameterized quantum circuits (PQCs) within quantum and hybrid convolutional neural network (HQNN and QCNN) architectures, applied to the task of satellite image…
• Deep Ensembling of Multiband Images for Earth Remote Sensing and Foramnifera Data
  2 Apr 2025 1 repository listed
  Two applications are illustrated in this work: (1) satellite image classification tested on the EuroSAT and LCZ42 datasets and (2) a species-level identification of planktic foraminifera.
• Improving Power Plant CO2 Emission Estimation with Deep Learning and Satellite/Simulated Data
  4 Feb 2025 1 repository listed
  CO2 emissions from power plants, as significant super emitters, contribute substantially to global warming.
• Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT Models
  5 Sep 2024 1 repository listed
  This study focuses on identifying the most effective pre-trained model for land use classification in onboard satellite processing, emphasizing achieving high accuracy, computational efficiency, and robustness against…
• Kolmogorov-Arnold Network for Satellite Image Classification in Remote Sensing
  2 Jun 2024 1 repository listed
  By utilizing the EuroSAT dataset, we provided a robust testbed to investigate whether KAN is suitable for remote sensing classification tasks.
• An Effective Weight Initialization Method for Deep Learning: Application to Satellite Image Classification
  1 Jun 2024 1 repository listed
  In this study, a novel weight initialization method is proposed in the context of satellite image classification.
• FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite Imagery
  3 Apr 2024 1 repository listed
  Object detection in remotely sensed satellite pictures is fundamental in many fields such as biophysical, and environmental monitoring.
• Diagnosing Model Performance Under Distribution Shift
  3 Mar 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In order to do this, we define a hypothetical distribution on X consisting of values common in both training and target, over which it is easy to compare Y |X and thus predictive performance.
• Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image Classification
  1 Feb 2021 1 repository listed
  A different classifier from the generator and the discriminator is used in the 3D-HyperGAMO model, which is trained using both original and generated samples to {determine} the classes of newly generated samples to…
• Classification and understanding of cloud structures via satellite images with EfficientUNet
  27 Sep 2020 1 repository listed
  Climate change has been a common interest and the forefront of crucial political discussion and decision-making for many years.
• An Open-source Tool for Hyperspectral Image Augmentation in Tensorflow
  30 Mar 2020 1 repository listed
  Tensorflow tool allows for rapid prototyping and testing of deep learning models, however, its built-in image generator is designed to handle a maximum of four spectral channels.
• DeepSat V2: Feature Augmented Convolutional Neural Nets for Satellite Image Classification
  15 Nov 2019 1 repository listed
  Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning.
• DeepSat - A Learning framework for Satellite Imagery
  11 Sep 2015 1 repository listed
  Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.