AIMC Topic: Neural Networks, Computer

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Automatic sleep stage classification: A light and efficient deep neural network model based on time, frequency and fractional Fourier transform domain features.

Artificial intelligence in medicine
This work proposed a novel method for automatic sleep stage classification based on the time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a single-channel electroencephalogram (EEG). Bidirectional long short-term...

Long short-term memory model - A deep learning approach for medical data with irregularity in cancer predication with tumor markers.

Computers in biology and medicine
BACKGROUND: Machine learning (ML) has emerged as a superior method for the analysis of large datasets. Application of ML is often hindered by incompleteness of the data which is particularly evident when approaching disease screening data due to vari...

A sequence-based two-layer predictor for identifying enhancers and their strength through enhanced feature extraction.

Journal of bioinformatics and computational biology
Enhancers are short regulatory DNA fragments that are bound with proteins called activators. They are free-bound and distant elements, which play a vital role in controlling gene expression. It is challenging to identify enhancers and their strength ...

Polish Court Ruling Classification Using Deep Neural Networks.

Sensors (Basel, Switzerland)
In this work, the problem of classifying Polish court rulings based on their text is presented. We use natural language processing methods and classifiers based on convolutional and recurrent neural networks. We prepared a dataset of 144,784 authenti...

Enhancing Detection Quality Rate with a Combined HOG and CNN for Real-Time Multiple Object Tracking across Non-Overlapping Multiple Cameras.

Sensors (Basel, Switzerland)
Multi-object tracking in video surveillance is subjected to illumination variation, blurring, motion, and similarity variations during the identification process in real-world practice. The previously proposed applications have difficulties in learni...

Intelligent Tracking of Mechanically Thrown Objects by Industrial Catching Robot for Automated In-Plant Logistics 4.0.

Sensors (Basel, Switzerland)
Industry 4.0 smart manufacturing systems are equipped with sensors, smart machines, and intelligent robots. The automated in-plant transportation of manufacturing parts through throwing and catching robots is an attempt to accelerate the transportati...

BioS2Net: Holistic Structural and Sequential Analysis of Biomolecules Using a Deep Neural Network.

International journal of molecular sciences
BACKGROUND: For decades, the rate of solving new biomolecular structures has been exceeding that at which their manual classification and feature characterisation can be carried out efficiently. Therefore, a new comprehensive and holistic tool for th...

Emulation of synaptic functions with low voltage organic memtransistor for hardware oriented neuromorphic computing.

Scientific reports
Here, various synaptic functions and neural network simulation based pattern-recognition using novel, solution-processed organic memtransistors (memTs) with an unconventional redox-gating mechanism are demonstrated. Our synaptic memT device using con...

Machine Vision and Intelligent Algorithm Based on Neural Network.

Computational intelligence and neuroscience
Neural network algorithms and intelligent algorithms are hot topics in the field of deep learning. In this study, the neural network algorithm and intelligence are optimized, and it is used in simulation experiments to improve the target image recogn...

Performance Analysis of Deep Learning Models for Binary Classification of Cancer Gene Expression Data.

Journal of healthcare engineering
The classification of patients as cancer and normal patients by applying the computational methods on their gene expression profiles is an extremely important task. Recently, deep learning models, mainly multilayer perceptron and convolutional neural...