Keyword

pixel classification

Description: An image interpretation task that assigns each pixel to a category, such as a land-cover class, based on its measured features.

Primary topic: Remote-Sensing Image Classification (33%)

OpenAlex ID: keywords/pixel-based-classification

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

2017 · Vijay Badrinarayanan, Alex Kendall, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 19,586

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

2014 · Chen, Liang-Chieh, Papandreou, George, et al. · arXiv (Cornell University) · 4,213

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Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification

2017 · Ignacio Arganda-Carreras, Verena Kaynig, et al. · Bioinformatics · 2,397

Large Kernel Matters — Improve Semantic Segmentation by Global Convolutional Network

2017 · Chao Peng, Xiangyu Zhang, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,750

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Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks

2013 · Dan C. Cireşan, Alessandro Giusti, et al. · Lecture notes in computer science · 1,535

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Adaptive Thresholding using the Integral Image

2007 · Derek Bradley, Gerhard Roth · Journal of Graphics Tools · 1,391

Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images

2012 · Dan Cireşan, Alessandro Giusti, et al. · neural information processing systems · 1,291

Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery

2011 · Soe W. Myint, Patricia Gober, et al. · Remote Sensing of Environment · 1,240

Ilastik: Interactive learning and segmentation toolkit

2011 · Christoph Sommer, Christoph Straehle, et al. · IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI) · 1,168

Per-Pixel Classification is Not All You Need for Semantic Segmentation

2021 · Cheng, Bowen, Schwing, Alexander G., et al. · arXiv (Cornell University) · 1,019

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Optimizing Intersection-Over-Union in Deep Neural Networks for Image Segmentation

2016 · Md Atiqur Rahman, Yang Wang · Lecture notes in computer science · 1,008

SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking

2020 · Dongyan Guo, Jun Wang, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 979

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Automated Pixel‐Level Pavement Crack Detection on 3D Asphalt Surfaces Using a Deep‐Learning Network

2017 · Allen Zhang, Kelvin C.P. Wang, et al. · Computer-Aided Civil and Infrastructure Engineering · 971

A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features

2010 · D Marín, A Aquino, et al. · IEEE Transactions on Medical Imaging · 929

Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis

2017 · Mariana Belgiu, Ovidiu Csillik · Remote Sensing of Environment · 924

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BIRCH: A New Data Clustering Algorithm and Its Applications

1997 · Tian Zhang, Raghu Ramakrishnan, et al. · Data Mining and Knowledge Discovery · 888

Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark

2017 · Emmanuel Maggiori, Yuliya Tarabalka, et al. · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · 873

Multiscale conditional random fields for image labeling

2004 · Xuming He, R.S. Zemel, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 843

Comparative study of retinal vessel segmentation methods on a new publicly available database

2004 · Meindert Niemeijer, Joes Staal, et al. · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 796

Hyperspectral Image Processing for Automatic Target Detection Applications

2003 · Dimitris G. Manolakis, David Marden, et al. · 766

Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms

2009 · J.R. Otukei, T. Blaschke · International Journal of Applied Earth Observation and Geoinformation · 756

SVM- and MRF-Based Method for Accurate Classification of Hyperspectral Images

2010 · Yuliya Tarabalka, Mathieu Fauvel, et al. · IEEE Geoscience and Remote Sensing Letters · 749

Advanced Spectral Classifiers for Hyperspectral Images: A review

2017 · Pedram Ghamisi, Javier Plaza, et al. · IEEE Geoscience and Remote Sensing Magazine · 675

A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring

2016 · Neha Joshi, Matthias Baumann, et al. · Remote Sensing · 671

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Mapping Spatial Patterns with Morphological Image Processing

2006 · Peter Vogt, Kurt H. Riitters, et al. · Landscape Ecology · 638

Works count: 5,884

Citation count: 144,000