AIMC Topic: Neural Networks, Computer

Clear Filters Showing 10971 to 10980 of 31376 articles

Video Super-Resolution Method Using Deformable Convolution-Based Alignment Network.

Sensors (Basel, Switzerland)
With the advancement of sensors, image and video processing have developed for use in the visual sensing area. Among them, video super-resolution (VSR) aims to reconstruct high-resolution sequences from low-resolution sequences. To use consecutive co...

Feature Pyramid U-Net with Attention for Semantic Segmentation of Forward-Looking Sonar Images.

Sensors (Basel, Switzerland)
Forward-looking sonar is a technique widely used for underwater detection. However, most sonar images have underwater noise and low resolution due to their acoustic properties. In recent years, the semantic segmentation model U-Net has shown excellen...

M1M2: Deep-Learning-Based Real-Time Emotion Recognition from Neural Activity.

Sensors (Basel, Switzerland)
Emotion recognition, or the ability of computers to interpret people's emotional states, is a very active research area with vast applications to improve people's lives. However, most image-based emotion recognition techniques are flawed, as humans c...

A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal.

Sensors (Basel, Switzerland)
In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A...

Gait Trajectory Prediction on an Embedded Microcontroller Using Deep Learning.

Sensors (Basel, Switzerland)
Achieving a normal gait trajectory for an amputee's active prosthesis is challenging due to its kinematic complexity. Accordingly, lower limb gait trajectory kinematics and gait phase segmentation are essential parameters in controlling an active pro...

Biomedical named entity recognition with the combined feature attention and fully-shared multi-task learning.

BMC bioinformatics
BACKGROUND: Biomedical named entity recognition (BioNER) is a basic and important task for biomedical text mining with the purpose of automatically recognizing and classifying biomedical entities. The performance of BioNER systems directly impacts do...

An emotion analysis in learning environment based on theme-specified drawing by convolutional neural network.

Frontiers in public health
Emotion in the learning process can directly influence the learner's attention, memory, and cognitive activities. Several literatures indicate that hand-drawn painting could reflect the learner's emotional status. But, such an evaluation of emotional...

MC-UNet: Multimodule Concatenation Based on U-Shape Network for Retinal Blood Vessels Segmentation.

Computational intelligence and neuroscience
Accurate retinal blood vessels segmentation is an important step in the clinical diagnosis of ophthalmic diseases. Many deep learning frameworks have come up for retinal blood vessels segmentation tasks. However, the complex vascular structure and un...

Neural network in food analytics.

Critical reviews in food science and nutrition
Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food supply chain and forecast $11.2 billion in agriculture markets. As a general-purpo...

Capturing advanced human cognitive abilities with deep neural networks.

Trends in cognitive sciences
How can artificial neural networks capture the advanced cognitive abilities of pioneering scientists? I suggest they must learn to exploit human-invented tools of thought and human-like ways of using them, and must engage in explicit goal-directed pr...