Search

Your search keyword '"Platos, Jan"' showing total 8 results
Start Over Author "Platos, Jan" Topic data mining
8 results on '"Platos, Jan"'

3. Lightweight Spectral–Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification.

Author

Roy, Swalpa Kumar, Chatterjee, Subhrasankar, Bhattacharyya, Siddhartha, Chaudhuri, Bidyut B., and Platos, Jan

Subjects
CONVOLUTIONAL neural networks, CUBES, BIG data, COMPUTER performance, THREE-dimensional imaging, CLASSIFICATION, ARTIFICIAL neural networks
Abstract

Of late, convolutional neural networks (CNNs) find great attention in hyperspectral image (HSI) classification since deep CNNs exhibit commendable performance for computer vision-related areas. CNNs have already proved to be very effective feature extractors, especially for the classification of large data sets composed of 2-D images. However, due to the existence of noisy or correlated spectral bands in the spectral domain and nonuniform pixels in the spatial neighborhood, HSI classification results are often degraded and unacceptable. However, the elementary CNN models often find intrinsic representation of pattern directly when employed to explore the HSI in the spectral–spatial domain. In this article, we design an end-to-end spectral–spatial squeeze-and-excitation (SE) residual bag-of-feature (S3EResBoF) learning framework for HSI classification that takes as input raw 3-D image cubes without engineering and builds a codebook representation of transform feature by motivating the feature maps facilitating classification by suppressing useless feature maps based on patterns present in the feature maps. To boost the classification performance and learn the joint spatial–spectral features, every residual block is connected to every other 3-D convolutional layer through an identity mapping followed by an SE block, thereby facilitating the rich gradients through backpropagation. Additionally, we introduce batch normalization on every convolutional layer (ConvBN) to regularize the convergence of the network and scale invariant BoF quantization for the measure of classification. The experiments conducted using three well-known HSI data sets and compared with the state-of-the-art classification methods reveal that S3EResBoF provides competitive performance in terms of both classification and computation time. [ABSTRACT FROM AUTHOR]

Published
2020
Full Text
View/download PDF

4. Analysis of Prediction Techniques for Temporal Data Based on Nonlinear Regression Model

Author

Sagar, Pinki, Gupta, Prinima, Kashyap, Indu, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Snasel, Vaclav, editor, Platos, Jan, editor, and Hassanien, Aboul Ella, editor

Published
2020
Full Text
View/download PDF

5. Prediction of Celiac Disease Using Machine-Learning Techniques

Author

Mehandiratta, Agrima, Vij, Neha, Khanna, Ashish, Gupta, Pooja, Gupta, Deepak, Gupta, Ayush Kumar, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Snasel, Vaclav, editor, Platos, Jan, editor, and Hassanien, Aboul Ella, editor

Published
2020
Full Text
View/download PDF

6. Adapting Machine Learning Techniques for Credit Card Fraud Detection

Author

Keswani, Bright, Vijay, Prity, Nayak, Narayan, Keswani, Poonam, Dash, Saumyaranjan, Sahoo, Laxman, Mishra, Tarini Ch., Mohapatra, Ambarish G., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Snasel, Vaclav, editor, Platos, Jan, editor, and Hassanien, Aboul Ella, editor

Published
2020
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results