Brain-inspired chips can slash AI energy use by as much as 100-fold, but the road to mainstream deployment is far from ...

Utilizing an autoencoder network, our model indirectly trains the photonic energy band and transmission spectrum, by converting them into feature coding. It integrates a transmission spectrum ...

Hi, Thanks for your great work with MAISI. The mask_generation_autoencoder has 8 input channels. What is the kind of data that is required as input? Would you have an example on how to use the mask ...

Due to the complexity of samples and the limitations in spatial resolution, the spectra in hyperspectral imaging (HSI) are generally contributed to by multiple components, making univariate analysis ...

Keywords: autoencoder (AE), Internet of Things, machine learning, particle swarm optimization, deep neural network Citation: Saheed YK, Usman AA, Sukat FD and Abdulrahman M (2023) A novel hybrid ...

This paper presents a dual autoencoder network model based on the retinex theory to perform the low-light enhancement and noise reduction by combining the stacked and convolutional autoencoders. The ...

Our proposed sparse autoencoder, and the deep-network is trained simultaneously for feature selection and improving classifier decision. Any further training to improve the classifier was done by ...