The results were published in Neural Networks. Like a river current, directional connections in neuronal networks propagate signals in a downstream flow from one area to another. A microfluid device ...

Imagine a world without disease. Sounds utopian? AI just made it a multibillion-dollar bet to discover drugs – and forget Big ...

Examples of deep models include Recurrent Neural Networks (RNNs), Deep Neural Networks (DNNs), and Convolutional Neural Networks (CNN). Among them, CNN is one of the most used models for image ...

In light of this, we have developed a recognition model for UAV using a dual-channel multi-scale convolutional neural network (CNN). This model initially enhances UAV recognition accuracy by ...

With the advancement of technology and the increase in user demands, gesture recognition played a pivotal role in the field of human-computer interaction. Among various sensing devices, Time-of-Flight ...

3.2 Convolutional neural network The proposed work employs CNN as a deep learning technique to classify OCT images to four categories. The first three categories include the mentioned diseases: DME, ...

A convolutional neural network is a multilayer supervised learning neural network, which consists of a convolution layer, a pooling layer, and a fully connected layer. (24) Its structure is shown in ...

Furthermore, recognizing the interdependencies between the three dimensions (Tran et al., 2015), we designed a compact 3D convolutional neural network (3D-CNN) model to learn the multivariate features ...