Ghostnet for Hyperspectral Image Classification

[1]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[2]  A F Goetz,et al.  Imaging Spectrometry for Earth Remote Sensing , 1985, Science.

[3]  C.-C. Jay Kuo.  Understanding convolutional neural networks with a mathematical model , 2016, J. Vis. Commun. Image Represent..

[4]  Zhou Guo,et al.  On combining multiscale deep learning features for the classification of hyperspectral remote sensing imagery , 2015 .

[5]  Hongbin Pu,et al.  Pathogenetic process monitoring and early detection of pear black spot disease caused by Alternaria alternata using hyperspectral imaging , 2019, Postharvest Biology and Technology.

[6]  Jon Atli Benediktsson,et al.  Sensitivity of Support Vector Machines to Random Feature Selection in Classification of Hyperspectral Data , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[7]  Didier Perrin,et al.  MIR spectral characterization of plastic to enable discrimination in an industrial recycling context: II. Specific case of polyolefins. , 2019, Waste management.

[8]  Jun Li,et al.  Active Learning With Convolutional Neural Networks for Hyperspectral Image Classification Using a New Bayesian Approach , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Samy Bengio,et al.  Links between perceptrons, MLPs and SVMs , 2004, ICML.

[10]  Yoshua Bengio,et al.  On the Properties of Neural Machine Translation: Encoder–Decoder Approaches , 2014, SSST@EMNLP.

[11]  Timothy A. Warner,et al.  Implementation of machine-learning classification in remote sensing: an applied review , 2018 .

[12]  Hayaru Shouno,et al.  Analysis of function of rectified linear unit used in deep learning , 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

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

[14]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[15]  Antonio J. Plaza,et al.  Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[16]  Xiangyu Zhang,et al.  ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design , 2018, ECCV.

[17]  D. Manolakis,et al.  Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms , 2016 .

[18]  Yoshua Bengio,et al.  Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.

[19]  Daniel Mozos,et al.  FPGA implementation of the principal component analysis algorithm for dimensionality reduction of hyperspectral images , 2019, Journal of Real-Time Image Processing.

[20]  Stephen K. Babey,et al.  A compact airborne spectrographic imager (CASI) , 1989 .

[21]  Antonio J. Plaza,et al.  Deep&Dense Convolutional Neural Network for Hyperspectral Image Classification , 2018, Remote. Sens..

[22]  Antonio J. Plaza,et al.  On Endmember Identification in Hyperspectral Images Without Pure Pixels: A Comparison of Algorithms , 2011, Journal of Mathematical Imaging and Vision.

[23]  Bo Chen,et al.  MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.

[24]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[25]  Paul Scheunders,et al.  Close range hyperspectral imaging of plants: A review , 2017 .

[26]  Tsehaie Woldai,et al.  Multi- and hyperspectral geologic remote sensing: A review , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[27]  Shutao Li,et al.  Feature Extraction With Multiscale Covariance Maps for Hyperspectral Image Classification , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[28]  Antonio J. Plaza,et al.  Fast Spatial Preprocessing for Spectral Unmixing of Hyperspectral Data on Graphics Processing Units , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[29]  Guigang Zhang,et al.  Deep Learning , 2016, Int. J. Semantic Comput..

[30]  Xudong Kang,et al.  Dual-Path Network-Based Hyperspectral Image Classification , 2019, IEEE Geoscience and Remote Sensing Letters.

[31]  Ying Li,et al.  Hyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Antonio J. Plaza,et al.  Fusion of hyperspectral and LiDAR data using morphological component analysis , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[33]  Kurt Keutzer,et al.  Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[34]  Alan R. Gillespie,et al.  Remote Sensing of Landscapes with Spectral Images: A Physical Modeling Approach , 2004 .

[35]  Alexander F. H. Goetz,et al.  Three decades of hyperspectral remote sensing of the Earth: a personal view. , 2009 .

[36]  Jianyuan Guo,et al.  GhostNet: More Features From Cheap Operations , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[37]  Fan Zhang,et al.  Deep Convolutional Neural Networks for Hyperspectral Image Classification , 2015, J. Sensors.

[38]  Thomas Wiatowski,et al.  A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction , 2015, IEEE Transactions on Information Theory.

[39]  Filiberto Pla,et al.  Capsule Networks for Hyperspectral Image Classification , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[40]  A. Gitelson,et al.  Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data. , 2012, Water research.

[41]  Andrew McCallum,et al.  Energy and Policy Considerations for Deep Learning in NLP , 2019, ACL.

[42]  Yoshua Bengio,et al.  Convolutional networks for images, speech, and time series , 1998 .

[43]  P. Atkinson,et al.  Introduction Neural networks in remote sensing , 1997 .

[44]  Lonneke Goddijn-Murphy,et al.  Concept for a hyperspectral remote sensing algorithm for floating marine macro plastics. , 2018, Marine pollution bulletin.

[45]  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.

[46]  Raphael M. Kudela,et al.  Application of hyperspectral remote sensing to cyanobacterial blooms in inland waters , 2015 .

[47]  Tao Zhang,et al.  A Survey of Model Compression and Acceleration for Deep Neural Networks , 2017, ArXiv.

[48]  J. G. Lyon,et al.  Hyperspectral Remote Sensing of Vegetation , 2011 .

[49]  Tao Li,et al.  HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image , 2018, 2018 International Conference on Audio, Language and Image Processing (ICALIP).

[50]  Heidi M. Dierssen,et al.  Sensing Ocean Plastics with an Airborne Hyperspectral Shortwave Infrared Imager. , 2018, Environmental science & technology.

[51]  Enhua Wu,et al.  Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[52]  S. Macenka,et al.  Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) , 1988 .

[53]  Sebastián López,et al.  Real-Time Hyperspectral Image Compression Onto Embedded GPUs , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[54]  B. Kunkel,et al.  ROSIS (Reflective Optics System Imaging Spectrometer) - A Candidate Instrument For Polar Platform Missions , 1988, Other Conferences.

[55]  Xueliang Zhang,et al.  Deep learning in remote sensing applications: A meta-analysis and review , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[56]  Raúl Rojas,et al.  Neural Networks - A Systematic Introduction , 1996 .

[57]  Antonio Plaza,et al.  Cloud implementation of logistic regression for hyperspectral image classification , 2018 .

[58]  Antonio Plaza,et al.  Low–High-Power Consumption Architectures for Deep-Learning Models Applied to Hyperspectral Image Classification , 2019, IEEE Geoscience and Remote Sensing Letters.

[59]  François Chollet,et al.  Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[60]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[61]  Antonio J. Plaza,et al.  Deep Pyramidal Residual Networks for Spectral–Spatial Hyperspectral Image Classification , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[62]  Jian Sun,et al.  Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[63]  Mercedes Eugenia Paoletti,et al.  Deep learning classifiers for hyperspectral imaging: A review , 2019 .