Hybrid 3D/2D Complete Inception Module and Convolutional Neural Network for Hyperspectral Remote Sensing Image Classification

[1]  A. Plaza,et al.  Multimodal Fusion Transformer for Remote Sensing Image Classification , 2022, ArXiv.

[2]  D. Hanbay,et al.  Classification of hyperspectral remote sensing images using different dimension reduction methods with 3D/2D CNN , 2022, Remote Sensing Applications: Society and Environment.

[3]  Muhammad Ahmad,et al.  A Fast and Compact 3-D CNN for Hyperspectral Image Classification , 2020, IEEE Geoscience and Remote Sensing Letters.

[4]  D. Hanbay,et al.  Creating a Parallel Corpora for Turkish-English Academic Translations , 2021, Computer Science.

[5]  Manuel Mazzara,et al.  Artifacts of different dimension reduction methods on hybrid CNN feature hierarchy for Hyperspectral Image Classification , 2021 .

[6]  Shyam Lal,et al.  Deep learning ensemble method for classification of satellite hyperspectral images , 2021, Remote Sensing Applications: Society and Environment.

[7]  D. Hanbay,et al.  4CF-Net: Hiperspektral uzaktan algılama görüntülerinin spektral uzamsal sınıflandırılması için yeni 3B evrişimli sinir ağı , 2021, Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi.

[8]  Manuel Mazzara,et al.  Regularized CNN Feature Hierarchy for Hyperspectral Image Classification , 2021, Remote. Sens..

[9]  Davut Hanbay,et al.  Classification of Hyperspectral Images Using 3D CNN Based ResNet50 , 2021, 2021 29th Signal Processing and Communications Applications Conference (SIU).

[10]  B. Gowtham,et al.  Hyperspectral Image Analysis using Principal Component Analysis and Siamese Network , 2021 .

[11]  Agus Lanini Et.al The Effectiveness of Customary Law to Protect Natural Resources in The National Park in Central Sulawesi , 2021 .

[12]  Yao Yang,et al.  Multiscale Residual Network With Mixed Depthwise Convolution for Hyperspectral Image Classification , 2021, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Davut Hanbay,et al.  Texture defect classification with multiple pooling and filter ensemble based on deep neural network , 2021, Expert Syst. Appl..

[14]  Adil Mehmood Khan,et al.  Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNN , 2021, ArXiv.

[15]  L. Bruzzone,et al.  Attention-Based Adaptive Spectral–Spatial Kernel ResNet for Hyperspectral Image Classification , 2020, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Dariush Abbasi-Moghadam,et al.  Hyperspectral Image Classification Using a Hybrid 3D-2D Convolutional Neural Networks , 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[17]  Antonio Plaza,et al.  Morphological Convolutional Neural Networks for Hyperspectral Image Classification , 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[18]  M. Venkatesan,et al.  HybridCNN based hyperspectral image classification using multiscale spatiospectral features , 2020 .

[19]  Lianru Gao,et al.  Hyperspectral Image Classification Based on a Shuffled Group Convolutional Neural Network with Transfer Learning , 2020, Remote. Sens..

[20]  Alkha Mohan,et al.  V3O2: hybrid deep learning model for hyperspectral image classification using vanilla-3D and octave-2D convolution , 2020, Journal of Real-Time Image Processing.

[21]  Shiv Ram Dubey,et al.  FuSENet: fused squeeze-and-excitation network for spectral-spatial hyperspectral image classification , 2020, IET Image Process..

[22]  N. Venugopal,et al.  Automatic Semantic Segmentation with DeepLab Dilated Learning Network for Change Detection in Remote Sensing Images , 2020, Neural Processing Letters.

[23]  Jan Platos,et al.  Lightweight Spectral–Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification , 2020, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Yi Liu,et al.  A Multi-Scale and Multi-Level Spectral-Spatial Feature Fusion Network for Hyperspectral Image Classification , 2020, Remote. Sens..

[25]  Yi Wang,et al.  Multiple Kernel-Based SVM Classification of Hyperspectral Images by Combining Spectral, Spatial, and Semantic Information , 2020, Remote. Sens..

[26]  Peng Fu,et al.  Hyperspectral Image Classification Method Based on 2D–3D CNN and Multibranch Feature Fusion , 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[27]  Hemant A. Patil,et al.  Novel Inception-GAN for Whispered-to-Normal Speech Conversion , 2019, 10th ISCA Workshop on Speech Synthesis (SSW 10).

[28]  Davut Hanbay,et al.  Automatic Thresholding Method Developed With Entropy For Fabric Defect Detection , 2019, 2019 International Artificial Intelligence and Data Processing Symposium (IDAP).

[29]  Licheng Jiao,et al.  Multipath Residual Network for Spectral-Spatial Hyperspectral Image Classification , 2019, Remote. Sens..

[30]  Adil Mehmood Khan,et al.  Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images , 2019, Remote. Sens..

[31]  Jocelyn Chanussot,et al.  Hyperspectral Classification Through Unmixing Abundance Maps Addressing Spectral Variability , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Xin Pan,et al.  Joint Deep Learning for land cover and land use classification , 2019, Remote Sensing of Environment.

[33]  Patrick Lambert,et al.  3-D Deep Learning Approach for Remote Sensing Image Classification , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[34]  Qian Du,et al.  Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks , 2018, Remote. Sens..

[35]  Shutao Li,et al.  Hyperspectral Image Classification With Deep Feature Fusion Network , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[36]  Seungmin Rho,et al.  Hyperspectral classification based on spectral-spatial convolutional neural networks , 2018, Eng. Appl. Artif. Intell..

[37]  Zhiming Luo,et al.  Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[38]  Bo Li,et al.  Multi-scale 3D deep convolutional neural network for hyperspectral image classification , 2017, 2017 IEEE International Conference on Image Processing (ICIP).

[39]  Shutao Li,et al.  Learning to Diversify Deep Belief Networks for Hyperspectral Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[40]  Ying Li,et al.  Spectral-Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network , 2017, Remote. Sens..

[41]  Chunhui Zhao,et al.  Spectral-Spatial Classification of Hyperspectral Imagery Based on Stacked Sparse Autoencoder and Random Forest , 2017 .

[42]  Linmi Tao,et al.  Efficient Deep Auto-Encoder Learning for the Classification of Hyperspectral Images , 2016, 2016 International Conference on Virtual Reality and Visualization (ICVRV).

[43]  Nikolaos Doulamis,et al.  Deep supervised learning for hyperspectral data classification through convolutional neural networks , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[44]  Jon Atli Benediktsson,et al.  Classification of Hyperspectral Images by Exploiting Spectral–Spatial Information of Superpixel via Multiple Kernels , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[45]  Xing Zhao,et al.  Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[46]  Gang Wang,et al.  Deep Learning-Based Classification of Hyperspectral Data , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[47]  Jon Atli Benediktsson,et al.  Spectral–Spatial Hyperspectral Image Classification via Multiscale Adaptive Sparse Representation , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[48]  Antonio J. Plaza,et al.  Semisupervised Hyperspectral Image Segmentation Using Multinomial Logistic Regression With Active Learning , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[49]  Yang Tao,et al.  Hyperspectral Image Classification Methods , 2010 .

[50]  Lorenzo Bruzzone,et al.  Kernel-based methods for hyperspectral image classification , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[51]  Joydeep Ghosh,et al.  Investigation of the random forest framework for classification of hyperspectral data , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[52]  Johannes R. Sveinsson,et al.  Classification of hyperspectral data from urban areas based on extended morphological profiles , 2005, IEEE Transactions on Geoscience and Remote Sensing.