AIMC Topic: Neural Networks, Computer

Clear Filters Showing 11531 to 11540 of 31376 articles

DAN-PD: Domain adaptive network with parallel decoder for polyp segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Endoscopy is essential for polyp diagnosis and prevention of colorectal cancer. Many deep learning methods have been proposed to perform automatic semantic segmentation of polyps in endoscopic images. However, labeled training images are always scarc...

Deep-Learning-Based Adaptive Symbol Decision for Visual MIMO System with Variable Channel Modeling.

Sensors (Basel, Switzerland)
A channel modeling method and deep-learning-based symbol decision method are proposed to improve the performance of a visual MIMO system for communication between a variable-color LED array and camera. Although image processing algorithms using color...

Recover User's Private Training Image Data by Gradient in Federated Learning.

Sensors (Basel, Switzerland)
Exchanging gradient is a widely used method in modern multinode machine learning system (e.g., distributed training, Federated Learning). Gradients and weights of model has been presumed to be safe to delivery. However, some studies have shown that g...

Rotating Single-Antenna Spoofing Signal Detection Method Based on IPNN.

Sensors (Basel, Switzerland)
The traditional carrier-phase differential detection technology mainly relies on the spatial processing method, which uses antenna arrays or moving antennas to detect spoofing signals, but it cannot be applied to static single-antenna receivers. Aimi...

Gait Recognition with Self-Supervised Learning of Gait Features Based on Vision Transformers.

Sensors (Basel, Switzerland)
Gait is a unique biometric trait with several useful properties. It can be recognized remotely and without the cooperation of the individual, with low-resolution cameras, and it is difficult to obscure. Therefore, it is suitable for crime investigati...

Loop Closure Detection Based on Residual Network and Capsule Network for Mobile Robot.

Sensors (Basel, Switzerland)
Loop closure detection based on a residual network (ResNet) and a capsule network (CapsNet) is proposed to address the problems of low accuracy and poor robustness for mobile robot simultaneous localization and mapping (SLAM) in complex scenes. First...

Developing a hybrid time-series artificial intelligence model to forecast energy use in buildings.

Scientific reports
The development of a reliable energy use prediction model is still difficult due to the inherent complex pattern of energy use data. There are few studies developing a prediction model for the one-day-ahead energy use prediction in buildings and opti...

Realization of optical logic gates using on-chip diffractive optical neural networks.

Scientific reports
Optical computing is highly desired as a potential strategy for circumventing the performance limitations of semiconductor-based electronic devices and circuits. Optical logic gates are considered as fundamental building blocks for optical computatio...

Graph-based representation for identifying individual travel activities with spatiotemporal trajectories and POI data.

Scientific reports
Individual daily travel activities (e.g., work, eating) are identified with various machine learning models (e.g., Bayesian Network, Random Forest) for understanding people's frequent travel purposes. However, labor-intensive engineering work is ofte...

Automated assessment of balance: A neural network approach based on large-scale balance function data.

Frontiers in public health
Balance impairment (BI) is an important cause of falls in the elderly. However, the existing balance estimation system needs to measure a large number of items to obtain the balance score and balance level, which is less efficient and redundant. In t...