AIMC Topic: Neural Networks, Computer

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A Data-Driven Model for Automated Chinese Word Segmentation and POS Tagging.

Computational intelligence and neuroscience
Chinese natural language processing tasks often require the solution of Chinese word segmentation and POS tagging problems. Traditional Chinese word segmentation and POS tagging methods mainly use simple matching algorithms based on lexicons and rule...

Dermoscopic image segmentation based on Pyramid Residual Attention Module.

PloS one
We propose a stacked convolutional neural network incorporating a novel and efficient pyramid residual attention (PRA) module for the task of automatic segmentation of dermoscopic images. Precise segmentation is a significant and challenging step for...

Artificial intelligence and machine learning applications in biopharmaceutical manufacturing.

Trends in biotechnology
Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption of AI-ML techniques include the growing global demand for biother...

Mammogram classification based on a novel convolutional neural network with efficient channel attention.

Computers in biology and medicine
Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosis (CAD) systems have achieved significant results in recent years, precise diagnosis of lesions in m...

Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks.

NeuroImage
Forming transformation-tolerant object representations is critical to high-level primate vision. Despite its significance, many details of tolerance in the human brain remain unknown. Likewise, despite the ability of convolutional neural networks (CN...

Super-resolution of brain tumor MRI images based on deep learning.

Journal of applied clinical medical physics
INTRODUCTION: To explore and evaluate the performance of MRI-based brain tumor super-resolution generative adversarial network (MRBT-SR-GAN) for improving the MRI image resolution in brain tumors.

Automatic whole blood cell analysis from blood smear using label-free multi-modal imaging with deep neural networks.

Analytica chimica acta
Whole blood cell analysis is widely used in medical applications since its results are indicators for diagnosing a series of diseases. In this work, we report automatic whole blood cell analysis from blood smear using label-free multi-modal imaging w...

Neuromorphic Tactile Edge Orientation Classification in an Unsupervised Spiking Neural Network.

Sensors (Basel, Switzerland)
Dexterous manipulation in robotic hands relies on an accurate sense of artificial touch. Here we investigate neuromorphic tactile sensation with an event-based optical tactile sensor combined with spiking neural networks for edge orientation detectio...

A Domestic Trash Detection Model Based on Improved YOLOX.

Sensors (Basel, Switzerland)
Domestic trash detection is an essential technology toward achieving a smart city. Due to the complexity and variability of urban trash scenarios, the existing trash detection algorithms suffer from low detection rates and high false positives, as we...

Deep Ensemble Fake News Detection Model Using Sequential Deep Learning Technique.

Sensors (Basel, Switzerland)
Recently, fake news has been widely spread through the Internet due to the increased use of social media for communication. Fake news has become a significant concern due to its harmful impact on individual attitudes and the community's behavior. Res...