AIMC Topic: Neural Networks, Computer

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Urine cell image recognition using a deep-learning model for an automated slide evaluation system.

BJU international
OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant).

The Application of Convolutional Neural Network Model in Diagnosis and Nursing of MR Imaging in Alzheimer's Disease.

Interdisciplinary sciences, computational life sciences
The disease Alzheimer is an irrepressible neurologicalbrain disorder. Earlier detection and proper treatment of Alzheimer's disease can help for brain tissue damage prevention. The study was intended to explore the segmentation effects of convolution...

Intelligent modeling and experimental study on methylene blue adsorption by sodium alginate-kaolin beads.

International journal of biological macromolecules
As tighter regulations on color in discharges to water bodies are more widely implemented worldwide, the demand for reliable inexpensive technologies for dye removal grows. In this study, the removal of the basic dye, methylene blue, by adsorption on...

Machine learning based disease prediction from genotype data.

Biological chemistry
Using results from genome-wide association studies for understanding complex traits is a current challenge. Here we review how genotype data can be used with different machine learning (ML) methods to predict phenotype occurrence and severity from ge...

Received Signal Strength Fingerprinting-Based Indoor Location Estimation Employing Machine Learning.

Sensors (Basel, Switzerland)
The fingerprinting technique is a popular approach to reveal location of persons, instruments or devices in an indoor environment. Typically based on signal strength measurement, a power level map is created first in the learning phase to align with ...

Review on the Application of Metalearning in Artificial Intelligence.

Computational intelligence and neuroscience
In recent years, artificial intelligence supported by big data has gradually become more dependent on deep reinforcement learning. However, the application of deep reinforcement learning in artificial intelligence is limited by prior knowledge and mo...

Multiscale Convolutional Neural Networks with Attention for Plant Species Recognition.

Computational intelligence and neuroscience
Plant species recognition is a critical step in protecting plant diversity. Leaf-based plant species recognition research is important and challenging due to the large within-class difference and between-class similarity of leaves and the rich incons...

Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm.

Computational intelligence and neuroscience
In this paper, a deep confidence neural network algorithm is used to design and deeply analyze the risk warning model for stadium operation. Many factors, such as video shooting angle, background brightness, diversity of features, and the relationshi...

PVRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Human motion prediction, which aims to predict future human poses given past poses, has recently seen increased interest. Many recent approaches are based on Recurrent Neural Networks (RNN) which model human poses with exponential maps. These approac...

Multi-Robot 2.5D Localization and Mapping Using a Monte Carlo Algorithm on a Multi-Level Surface.

Sensors (Basel, Switzerland)
Most indoor environments have wheelchair adaptations or ramps, providing an opportunity for mobile robots to navigate sloped areas avoiding steps. These indoor environments with integrated sloped areas are divided into different levels. The multi-lev...