AIMC Topic: Neural Networks, Computer

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INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network.

ISA transactions
Testing is one of the important methodologies used by various countries in order to fight against COVID-19 infection. The infection is considered as one of the deadliest ones although the mortality rate is not very high. COVID-19 infection is being c...

Deep learning-based simultaneous registration and unsupervised non-correspondence segmentation of medical images with pathologies.

International journal of computer assisted radiology and surgery
PURPOSE: The registration of medical images often suffers from missing correspondences due to inter-patient variations, pathologies and their progression leading to implausible deformations that cause misregistrations and might eliminate valuable inf...

Deep-Learning-Based Parking Area and Collision Risk Area Detection Using AVM in Autonomous Parking Situation.

Sensors (Basel, Switzerland)
In this paper, I propose a bird eye view image detection method for parking areas and collision risk areas at the same time in parking situations. Deep learning algorithms using area detection and semantic segmentation were used. The main architectur...

Railway Track Inspection Using Deep Learning Based on Audio to Spectrogram Conversion: An on-the-Fly Approach.

Sensors (Basel, Switzerland)
The periodic inspection of railroad tracks is very important to find structural and geometrical problems that lead to railway accidents. Currently, in Pakistan, rail tracks are inspected by an acoustic-based manual system that requires a railway engi...

Unsupervised Learning in Drug Design from Self-Organization to Deep Chemistry.

International journal of molecular sciences
The availability of computers has brought novel prospects in drug design. Neural networks (NN) were an early tool that cheminformatics tested for converting data into drugs. However, the initial interest faded for almost two decades. The recent succe...

Accurate Physical Property Predictions via Deep Learning.

Molecules (Basel, Switzerland)
Neural networks and deep learning have been successfully applied to tackle problems in drug discovery with increasing accuracy over time. There are still many challenges and opportunities to improve molecular property predictions with satisfactory ac...

Two-dimensional CNN-based distinction of human emotions from EEG channels selected by multi-objective evolutionary algorithm.

Scientific reports
In this study we explore how different levels of emotional intensity (Arousal) and pleasantness (Valence) are reflected in electroencephalographic (EEG) signals. We performed the experiments on EEG data of 32 subjects from the DEAP public dataset, wh...

Detection of Breast Cancer Using Histopathological Image Classification Dataset with Deep Learning Techniques.

BioMed research international
Cancer is one of the top causes of mortality, and it arises when cells in the body grow abnormally, like in the case of breast cancer. For people all around the world, it has now become a huge issue and a threat to their safety and wellbeing. Breast ...

Distance Field-Based Convolutional Neural Network for Edge Detection.

Computational intelligence and neuroscience
In this paper, we first propose an accurate edge detector using a distance field-based convolutional neural network (DF-CNN). In recent years, CNNs have been proved to be effective in image processing and computer vision. As edge detection is a funda...

3-Dimensional convolutional neural networks for predicting StarCraft Ⅱ results and extracting key game situations.

PloS one
In real-time strategy games, players collect resources, control various units, and create strategies to win. The creation of winning strategies requires accurately analyzing previous games; therefore, it is important to be able to identify the key si...