AIMC Topic: Neural Networks, Computer

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Systematic Review of Electricity Demand Forecast Using ANN-Based Machine Learning Algorithms.

Sensors (Basel, Switzerland)
The forecast of electricity demand has been a recurrent research topic for decades, due to its economical and strategic relevance. Several Machine Learning (ML) techniques have evolved in parallel with the complexity of the electric grid. This paper ...

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

Scientific reports
With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerned on the current classification system of International Classification of Diseases, Tenth Revision (...

Micro-CT image denoising with an asymmetric perceptual convolutional network.

Physics in medicine and biology
Micro-CT has important applications in biomedical research due to its ability to perform high-precision 3D imaging of micro-architecture in a non-invasive way. Because of the limited power of the radiation source, it is difficult to obtain a high sig...

Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology.

PLoS computational biology
There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) an...

Quadruplet-Based Deep Cross-Modal Hashing.

Computational intelligence and neuroscience
Recently, benefitting from the storage and retrieval efficiency of hashing and the powerful discriminative feature extraction capability of deep neural networks, deep cross-modal hashing retrieval has drawn more and more attention. To preserve the se...

Multi-Task Head Pose Estimation in-the-Wild.

IEEE transactions on pattern analysis and machine intelligence
We present a deep learning-based multi-task approach for head pose estimation in images. We contribute with a network architecture and training strategy that harness the strong dependencies among face pose, alignment and visibility, to produce a top ...

Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization.

IEEE transactions on pattern analysis and machine intelligence
Compared with global average pooling in existing deep convolutional neural networks (CNNs), global covariance pooling can capture richer statistics of deep features, having potential for improving representation and generalization abilities of deep C...

CNN-LRP: Understanding Convolutional Neural Networks Performance for Target Recognition in SAR Images.

Sensors (Basel, Switzerland)
Target recognition is one of the most challenging tasks in synthetic aperture radar (SAR) image processing since it is highly affected by a series of pre-processing techniques which usually require sophisticated manipulation for different data and co...

Deep Learning Based Prediction on Greenhouse Crop Yield Combined TCN and RNN.

Sensors (Basel, Switzerland)
Currently, greenhouses are widely applied for plant growth, and environmental parameters can also be controlled in the modern greenhouse to guarantee the maximum crop yield. In order to optimally control greenhouses' environmental parameters, one ind...

A Comparison of Three Neural Network Approaches for Estimating Joint Angles and Moments from Inertial Measurement Units.

Sensors (Basel, Switzerland)
The application of artificial intelligence techniques to wearable sensor data may facilitate accurate analysis outside of controlled laboratory settings-the holy grail for gait clinicians and sports scientists looking to bridge the lab to field divid...