AIMC Topic: Neural Networks, Computer

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Adversarial Joint-Learning Recurrent Neural Network for Incomplete Time Series Classification.

IEEE transactions on pattern analysis and machine intelligence
Incomplete time series classification (ITSC) is an important issue in time series analysis since temporal data often has missing values in practical applications. However, integrating imputation (replacing missing data) and classification within a mo...

A Neural Network Approach for Property Determination of Molecular Solar Cell Candidates.

The journal of physical chemistry. A
The dihydroazulene/vinylheptafulvene (DHA/VHF) photocouple is a promising candidate for molecular solar heat batteries, storing and releasing energy in a closed cycle. Much work has been done on improving the energy storage capacity and the half-life...

Intelligent Defect Diagnosis of Rolling Element Bearings under Variable Operating Conditions Using Convolutional Neural Network and Order Maps.

Sensors (Basel, Switzerland)
Vibration analysis is an established method for fault detection and diagnosis of rolling element bearings. However, it is an expert oriented exercise. To relieve the experts, the use of Artificial Intelligence (AI) techniques such as deep neural netw...

A Pruning Method for Deep Convolutional Network Based on Heat Map Generation Metrics.

Sensors (Basel, Switzerland)
With the development of deep learning, researchers design deep network structures in order to extract rich high-level semantic information. Nowadays, most popular algorithms are designed based on the complexity of visible image features. However, com...

A Broad Learning System to Predict the 28-Day Mortality of Patients Hospitalized with Community-Acquired Pneumonia: A Case-Control Study.

Computational and mathematical methods in medicine
This study was to conduct a model based on the broad learning system (BLS) for predicting the 28-day mortality of patients hospitalized with community-acquired pneumonia (CAP). A total of 1,210 eligible CAP cases from Chifeng Municipal Hospital were ...

Simultaneous vehicle and lane detection via MobileNetV3 in car following scene.

PloS one
Aiming at vehicle and lane detections on road scene, this paper proposes a vehicle and lane line joint detection method suitable for car following scenes. This method uses the codec structure and multi-task ideas, shares the feature extraction networ...

Effect of Training Data Volume on Performance of Convolutional Neural Network Pneumothorax Classifiers.

Journal of digital imaging
Large datasets with high-quality labels required to train deep neural networks are challenging to obtain in the radiology domain. This work investigates the effect of training dataset size on the performance of deep learning classifiers, focusing on ...

Designing sensitive viral diagnostics with machine learning.

Nature biotechnology
Design of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome's conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learne...

Mass excess estimations using artificial neural networks.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Mass excess knowledge is important to investigate the fundamental properties of atomic nuclei. It is a meaningful and important parameter for the determinations of nucleon binding energy, nuclear reaction Q value, energy threshold and plays an undeni...

COVID-19 image classification using deep learning: Advances, challenges and opportunities.

Computers in biology and medicine
Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected the lives of millions around the world. Chest X-Ray (CXR) and Computed Tomography (CT) ima...