Media Technology papers
Pofolia’s corpus holds 69 papers from Media Technology (2012–2026), each with a short summary. Below, the 20 most-cited, then the most recently added.
At a glance
- Most cited: Smart Cities: Definitions, Dimensions, Performance, and Initiatives (2015, 3,438 citations).
- The 20 papers listed have 49,421 citations between them.
- 14 of the 16 with a known journal quartile appeared in a Q1 journal.
- 3 have a free full text (open access).
- Most frequent journals: IEEE Geoscience and Remote Sensing Magazine, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing.
- Published between 2012 and 2020.
Most cited
Ranked by citation count. Because citations accumulate over time, this list naturally leans towards work published a few years ago; for where the field is now, see “recently added”. How to read the signals
Smart Cities: Definitions, Dimensions, Performance, and Initiatives
Journal of Urban Technology · 2015 · Q1 · SJR 1.00 · FWCI 190.01 · 3,438 citations
This paper clarifies the definition of a 'smart city' by synthesizing existing literature and official documents, identifying its key dimensions and performance metrics.
Digital communications : fundamentals and applications
2017 · FWCI 90.94 · 3,143 citations
This textbook offers an exceptionally accessible and mathematically precise introduction to digital communications, structuring complex concepts within a unified block diagram framework.
Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources
IEEE Geoscience and Remote Sensing Magazine · 2017 · Q1 · SJR 4.00 · FWCI 131.44 · 3,043 citations
This review analyzes the challenges and recent advances of applying deep learning to remote sensing data, aiming to simplify its adoption for scientists.
The role of artificial intelligence in achieving the Sustainable Development Goals
Nature Communications · 2020 · Q1 · SJR 4.00 · FWCI 134.41 · 2,975 citations · Open access
Artificial intelligence (AI) can significantly aid in achieving 134 targets across all Sustainable Development Goals, but it also poses a risk of inhibiting 59 targets, according to a consensus-based expert assessment.
Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks
IEEE Transactions on Geoscience and Remote Sensing · 2016 · Q1 · SJR 2.00 · FWCI 162.02 · 2,921 citations
A novel regularized deep feature extraction method using 3-D CNNs and virtual sample enhancement is proposed for hyperspectral image classification, achieving competitive results against state-of-the-art methods.
Deep learning in remote sensing: A comprehensive review and list of resources
Open MIND · 2017 · FWCI 163.35 · 2,813 citations
This review analyzes the challenges and recent advances of using deep learning for remote sensing data analysis, advocating for its application to large-scale challenges like climate change and urbanization.
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2012 · Q1 · SJR 1.00 · FWCI 277.00 · 2,755 citations
This paper provides a comprehensive overview of hyperspectral unmixing techniques, categorizing them into geometrical, statistical, sparsity-based, and spatial-contextual approaches.
Deep Learning-Based Classification of Hyperspectral Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2014 · Q1 · SJR 1.00 · FWCI 111.88 · 2,656 citations
This paper introduces deep learning, specifically stacked autoencoders, for hyperspectral data classification, achieving competitive performance by merging spectral and spatial features.
Remote Sensing Image Scene Classification: Benchmark and State of the Art
Proceedings of the IEEE · 2017 · Q1 · SJR 5.00 · FWCI 109.20 · 2,576 citations
This paper introduces NWPU-RESISC45, a new large-scale benchmark dataset for remote sensing image scene classification, containing 31,500 images across 45 classes, designed to overcome limitations of existing datasets.
Understanding Smart Cities: An Integrative Framework
2012 · 2,515 citations
This paper proposes a new integrative framework to understand smart cities, identifying eight critical factors that shape these initiatives.
Deep learning in remote sensing applications: A meta-analysis and review
ISPRS Journal of Photogrammetry and Remote Sensing · 2019 · Q1 · SJR 3.00 · FWCI 36.88 · 2,326 citations
This meta-analysis and review synthesizes over 200 recent publications on deep learning (DL) applications in remote sensing, revealing trends in study targets, DL models, spatial resolutions, and classification accuracy.
Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art
IEEE Geoscience and Remote Sensing Magazine · 2016 · Q1 · SJR 4.00 · FWCI 150.13 · 2,196 citations
This tutorial outlines a general framework for applying deep learning (DL) to remote sensing (RS) data, demonstrating its versatility across tasks from image preprocessing to scene understanding.
The culture of connectivity: a critical history of social media
Choice Reviews Online · 2013 · 2,161 citations
This book offers a critical history of social media, examining how platforms engineer sociality, make connectivity a resource, and shape user interactions through their design and economic structures.
AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification
IEEE Transactions on Geoscience and Remote Sensing · 2017 · Q1 · SJR 2.00 · FWCI 82.81 · 2,126 citations
A new large-scale dataset, AID, has been released for aerial scene classification, featuring over 10,000 annotated images to overcome limitations of existing smaller datasets.
Hyperspectral Remote Sensing Data Analysis and Future Challenges
IEEE Geoscience and Remote Sensing Magazine · 2013 · Q1 · SJR 4.00 · FWCI 139.62 · 2,105 citations
Hyperspectral remote sensing offers high-resolution Earth surface data for material identification and parameter estimation, but faces challenges from high dimensionality, spectral mixing, and noise.
Fast Feature Pyramids for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2014 · Q1 · SJR 4.00 · FWCI 307.66 · 2,029 citations
A new method approximates finely-sampled feature pyramids for object detection by extrapolating from features computed at octave-spaced scales, achieving state-of-the-art accuracy at significantly reduced computational cost.
Implementation of machine-learning classification in remote sensing: an applied review
International Journal of Remote Sensing · 2018 · Q2 · FWCI 89.42 · 1,969 citations · Open access
This review provides a practical overview of implementing machine learning for classifying remote sensing data, focusing on mature algorithms like SVMs, Random Forests, and neural networks.
U2Fusion: A Unified Unsupervised Image Fusion Network
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2020 · Q1 · SJR 4.00 · FWCI 60.37 · 1,909 citations
U2Fusion is a novel deep learning network that unifies multiple image fusion tasks (multi-modal, multi-exposure, multi-focus) into a single, unsupervised framework, eliminating the need for ground-truth data.
Deep Convolutional Neural Networks for Hyperspectral Image Classification
Journal of Sensors · 2015 · Q2 · FWCI 81.23 · 1,887 citations · Open access
A novel deep convolutional neural network (CNN) architecture directly classifies hyperspectral images in the spectral domain, outperforming traditional methods.
DenseFuse: A Fusion Approach to Infrared and Visible Images
IEEE Transactions on Image Processing · 2018 · Q1 · SJR 2.00 · FWCI 39.62 · 1,878 citations
A novel deep learning architecture, DenseFuse, has been developed to fuse infrared and visible images, achieving state-of-the-art performance.
Recently added
Deep learning recognises antibiotic modes of action from brightfield images
Nature Communications · 2026 · Q1 · SJR 4.00 · FWCI 3.23 · 2 citations · Open access
A deep learning model accurately identifies antibiotic modes of action (MoAs) from unlabelled brightfield microscopy images of E. coli, achieving 100% MoA recognition with a model trained on just 644 images and identifying novel MoAs with AUC > 0.75 for 5 out of 6 tested.
SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer
IEEE/CAA Journal of Automatica Sinica · 2022 · Q1 · SJR 3.00 · FWCI 97.95 · 1,326 citations
SwinFusion, a novel image fusion framework, uses a Swin Transformer and attention-guided cross-domain learning to integrate complementary information and global context, achieving superior performance across multi-modal and digital photography fusion tasks.
Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2022 · 988 citations
A novel TarDAL network fuses infrared and visible images for object detection by preserving infrared target structure and visible texture details, achieving higher detection mAP than state-of-the-art.
Augmented reality and virtual reality displays: emerging technologies and future perspectives
Light Science & Applications · 2021 · Q1 · SJR 4.00 · FWCI 78.35 · 1,244 citations · Open access
Holographic optical elements (HOEs) and lithography-enabled devices offer innovative solutions to overcome optical engineering challenges in compact and lightweight AR/VR near-eye displays, matching human vision performance.
Remote Sensing Image Change Detection With Transformers
IEEE Transactions on Geoscience and Remote Sensing · 2021 · Q1 · SJR 2.00 · FWCI 55.80 · 1,029 citations
A novel bitemporal image transformer (BIT) efficiently models spatial-temporal contexts for remote sensing change detection, outperforming convolutional and attention-based methods with significantly lower computational costs.
Global land use / land cover with Sentinel 2 and deep learning
2021 · 1,264 citations
A novel deep learning model trained on over 5 billion human-labeled Sentinel-2 pixels generates a global land use/land cover (LULC) map at 10m resolution with state-of-the-art accuracy.
SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers
arXiv (Cornell University) · 2021 · 1,201 citations · Open access
SpectralFormer, a novel transformer backbone, achieves superior hyperspectral image classification by learning spectrally local sequence information and fusing shallow layer features via cross-layer skip connections.
SNUNet-CD: A Densely Connected Siamese Network for Change Detection of VHR Images
IEEE Geoscience and Remote Sensing Letters · 2021 · Q1 · SJR 1.00 · FWCI 62.07 · 1,066 citations
SNUNet-CD, a densely connected Siamese network, improves very high-resolution (VHR) satellite image change detection by integrating shallow-layer features with deep semantic features, outperforming state-of-the-art methods in accuracy and computational efficiency.
Journals in this field
The journals that publish most of this field’s papers. Quartile (Q1–Q4), SJR and h-index are from SCImago Journal Rank; “in this field” is how many of the journal’s pooled papers belong here. What is a Q1 journal? · What is the h-index?
| Journal | Quartile | SJR | h-index | In this field | Summaries |
|---|---|---|---|---|---|
| IEEE Transactions on Geoscience and Remote Sensing | Q1 | 2.00 | 342 | 14 | 16 |
| IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Q1 | 1.00 | 151 | 5 | 5 |
| IEEE Transactions on Image Processing | Q1 | 2.00 | 363 | 4 | 11 |
| Remote Sensing | Q1 | 1.00 | 246 | 4 | 6 |
| IEEE Geoscience and Remote Sensing Magazine | Q1 | 4.00 | 78 | 3 | 4 |
| ISPRS Journal of Photogrammetry and Remote Sensing | Q1 | 3.00 | 221 | 3 | 4 |
| Proceedings of the IEEE | Q1 | 5.00 | 352 | 2 | 17 |
| IEEE Transactions on Pattern Analysis and Machine Intelligence | Q1 | 4.00 | 460 | 2 | 27 |
Every journal in Media Technology (Q1–Q4) →
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