Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

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 ...

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology ...

The computational model in (A) convolutional neural network (CNN) and the (B) convolutional neural network within spiking neural network (ConvSNN). We propose a novel data flow for the PIM-based ...

In recent years, Convolutional Neural Network (CNN), as a deep learning algorithm, has been widely used in many fields such as computer vision and speech recognition. In the field of geological ...

The schematic diagram of the test section is shown in Figure 2. The narrow channel with a rectangular cross-section is composed of two pieces of glass. The cross-sectional size is 30 × 1.5 mm, and the ...

In this letter, two convolutional neural network (CNN) models for detection of magnetic anomaly target signals are proposed. One is a 1-D CNN combined with signal feature (SF-CNN1D), and the other is ...