Several text classification tasks such as sentiment analysis, news categorization, multi-label and opinion are challenging problems even for modern deep learning networks. Recently, Capsule Networks (CapsNets) proposed image classification. It has been shown that CapsNets have several advantages over Convolutional Neural (CNNs), while their validity in the domain of was less explored. In this p...

Audio classification has been one of the most popular applications Artificial Neural Networks. This process is at center modern AI technology, such as virtual assistants, automatic speech recognition, and text-to-speech applications. There have studies about spoken digit its However, to best author's knowledge, very few works focusing on English recognition that implemented ANN done. In this st...

A crop image classification using convolutional neural network is proposed in the paper. Classification of images important and required many applications such as yield prediction, decease detection etc. (Yang et al., 2020)(Kavitha 2022). The main challenges are availability large dataset extraction meaningful features to describe a class image(Barbedo, 2018). We have pre-trained models like VG...

Abstract The traditional deep learning method has a large amount of calculation, long time training and complex network structure, which is not easy to be applied embedded or mobile devices. To solve the these problems, we proposed an improved lightweight named as Mobilenet-RseSK for skin disease classification. Firstly, new attention mechanism seSK module proposed, used replace position SE in ...