AIMC Topic: Neural Networks, Computer

Clear Filters Showing 11841 to 11850 of 31376 articles

Unsupervised SAR Imagery Feature Learning with Median Filter-Based Loss Value.

Sensors (Basel, Switzerland)
The scarcity of open SAR (Synthetic Aperture Radars) imagery databases (especially the labeled ones) and sparsity of pre-trained neural networks lead to the need for heavy data generation, augmentation, or transfer learning usage. This paper describe...

Cross-Modal Reconstruction for Tactile Signal in Human-Robot Interaction.

Sensors (Basel, Switzerland)
A human can infer the magnitude of interaction force solely based on visual information because of prior knowledge in human-robot interaction (HRI). A method of reconstructing tactile information through cross-modal signal processing is proposed in t...

Comparison of Graph Fitting and Sparse Deep Learning Model for Robot Pose Estimation.

Sensors (Basel, Switzerland)
The paper presents a simple, yet robust computer vision system for robot arm tracking with the use of RGB-D cameras. Tracking means to measure in real time the robot state given by three angles and with known restrictions about the robot geometry. Th...

A Joint Automatic Modulation Classification Scheme in Spatial Cognitive Communication.

Sensors (Basel, Switzerland)
Automatic modulation discrimination (AMC) is one of the critical technologies in spatial cognitive communication systems. Building a high-performance AMC model in intelligent receivers can help to realize adaptive signal synchronization and demodulat...

BRefine: Achieving High-Quality Instance Segmentation.

Sensors (Basel, Switzerland)
Instance segmentation has been developing rapidly in recent years. Mask R-CNN, a two-stage instance segmentation approach, has demonstrated exceptional performance. However, the masks are still very coarse. The downsampling operation of the backbone ...

End-to-End Continuous/Discontinuous Feature Fusion Method with Attention for Rolling Bearing Fault Diagnosis.

Sensors (Basel, Switzerland)
Mechanical equipment failure may cause massive economic and even life loss. Therefore, the diagnosis of the failures of machine parts in time is crucial. The rolling bearings are one of the most valuable parts, which have attracted the focus of fault...

PassTCN-PPLL: A Password Guessing Model Based on Probability Label Learning and Temporal Convolutional Neural Network.

Sensors (Basel, Switzerland)
The frequent incidents of password leakage have increased people's attention and research on password security. Password guessing is an essential part of password cracking and password security research. The progression of deep learning technology pr...

Multi-Level Classification of Driver Drowsiness by Simultaneous Analysis of ECG and Respiration Signals Using Deep Neural Networks.

International journal of environmental research and public health
The high number of fatal crashes caused by driver drowsiness highlights the need for developing reliable drowsiness detection methods. An ideal driver drowsiness detection system should estimate multiple levels of drowsiness accurately without interv...

Empirical Analysis of Early Childhood Enlightenment Education Using Neural Network.

Computational intelligence and neuroscience
This exploration aims to study the value orientation and essence of early childhood enlightenment education based on the deep neural network (DNN). Based on the acquisition and feature learning of cross-media education big data, the DNN correlation l...

Research on the Analysis of Correlation Factors of English Translation Ability Improvement Based on Deep Neural Network.

Computational intelligence and neuroscience
This paper adopts the algorithm of the deep neural network to conduct in-depth research and analysis on the factors associated with the improvement of English translation ability. This study focuses on text complexity, adding discourse complexity fea...