Currency detection and recognition based on deep learning
Q Zhang, WQ Yan - … on Advanced Video and Signal Based …, 2018 - ieeexplore.ieee.org
In recent years, deep learning has become the most popular research direction. It mainly
trains the dataset through neural networks. There are many different models that can be …
trains the dataset through neural networks. There are many different models that can be …
Fast economic dispatch in smart grids using deep learning: An active constraint screening approach
In smart grids, the power supply and demand are balanced through the electricity market to
promote the maximization of social welfare. An important procedure in electricity market …
promote the maximization of social welfare. An important procedure in electricity market …
Morphological attribute profile cube and deep random forest for small sample classification of hyperspectral image
B Liu, W Guo, X Chen, K Gao, X Zuo, R Wang… - IEEE Access, 2020 - ieeexplore.ieee.org
Deep learning based methods have made great progress in hyperspectral image
classification. However, training a deep learning model often requires a large number of …
classification. However, training a deep learning model often requires a large number of …
Nondestructive freshness discriminating of shrimp using visible/near-infrared hyperspectral imaging technique and deep learning algorithm
X Yu, L Tang, X Wu, H Lu - Food analytical methods, 2018 - Springer
In this study, visible and near-infrared hyperspectral imaging (HSI) technique combined with
deep learning algorithm was investigated for discriminating the freshness of shrimp during …
deep learning algorithm was investigated for discriminating the freshness of shrimp during …
Domain adaptation using representation learning for the classification of remote sensing images
Traditional machine learning (ML) techniques are often employed to perform complex
pattern recognition tasks for remote sensing images, such as land-use classification. In order …
pattern recognition tasks for remote sensing images, such as land-use classification. In order …
Medical image denoising system based on stacked convolutional autoencoder for enhancing 2-dimensional gel electrophoresis noise reduction
AS Ahmed, WH El-Behaidy, AAA Youssif - Biomedical Signal Processing …, 2021 - Elsevier
Image denoising is the technique of removing noise or distortions from an image. During
medical image acquisition, random noise is added, which results in a lower contrast in those …
medical image acquisition, random noise is added, which results in a lower contrast in those …
A novel systolic parallel hardware architecture for the FPGA acceleration of feedforward neural networks
LD Medus, T Iakymchuk, JV Frances-Villora… - IEEE …, 2019 - ieeexplore.ieee.org
New chips for machine learning applications appear, they are tuned for a specific topology,
being efficient by using highly parallel designs at the cost of high power or large complex …
being efficient by using highly parallel designs at the cost of high power or large complex …
A review of different dimensionality reduction methods for the prediction of sugar content from hyperspectral images of wine grape berries
R Silva, P Melo-Pinto - Applied Soft Computing, 2021 - Elsevier
Several dimensionality reduction techniques were applied to hyperspectral reflectance
images of wine grape berries, leading a study of the machine learning models' efficiency in …
images of wine grape berries, leading a study of the machine learning models' efficiency in …
Deep multiscale spectral-spatial feature fusion for hyperspectral images classification
Learning representative and discriminative feature that make full use of spectral-spatial
information is of cardinal significance for hyperspectral imagery (HSI) interpretation. In this …
information is of cardinal significance for hyperspectral imagery (HSI) interpretation. In this …
Resolution reconstruction classification: Fully octave convolution network with pyramid attention mechanism for hyperspectral image classification
Y Sun, B Liu, X Yu, A Yu, Z Xue… - International Journal of …, 2022 - Taylor & Francis
We propose a fully octave convolution network with a pyramid attention mechanism
(FOctConvPA) for whole Hyperspectral Image (HSI) classification. Because of the spatial …
(FOctConvPA) for whole Hyperspectral Image (HSI) classification. Because of the spatial …