AIMC Topic: Deep Learning

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Facility Layout Optimization of Urban Public Sports Services under the Background of Deep Learning.

Computational intelligence and neuroscience
The spatial layout and optimization of social facilities for sports are related to many factors such as urban economy, transportation, population, and urban planning. With the rapid development of artificial intelligence today, deep learning came int...

Effectiveness Analysis of English Newspaper Reading Teaching Based on Deep Learning from the Perspective of Online and Offline Hybrid Teaching.

Computational and mathematical methods in medicine
In recent years, China's higher education has developed rapidly, and the overall English proficiency of college students has improved significantly. In order to improve the English proficiency of students in higher education, English newspaper readin...

Auxiliary Pneumonia Classification Algorithm Based on Pruning Compression.

Computational and mathematical methods in medicine
Pneumonia infection is the leading cause of death in young children. The commonly used pneumonia detection method is that doctors diagnose through chest X-ray, and external factors easily interfere with the results. Assisting doctors in diagnosing pn...

Enhancer-LSTMAtt: A Bi-LSTM and Attention-Based Deep Learning Method for Enhancer Recognition.

Biomolecules
Enhancers are short DNA segments that play a key role in biological processes, such as accelerating transcription of target genes. Since the enhancer resides anywhere in a genome sequence, it is difficult to precisely identify enhancers. We presented...

Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study.

European radiology
OBJECTIVE: Ultra-high-resolution CT (UHR-CT), which can be applied normal resolution (NR), high-resolution (HR), and super-high-resolution (SHR) modes, has become available as in conjunction with multi-detector CT (MDCT). Moreover, deep learning reco...

PDE-READ: Human-readable partial differential equation discovery using deep learning.

Neural networks : the official journal of the International Neural Network Society
PDE discovery shows promise for uncovering predictive models of complex physical systems but has difficulty when measurements are noisy and limited. We introduce a new approach for PDE discovery that uses two Rational Neural Networks and a principled...

Cardiac MRI segmentation with sparse annotations: Ensembling deep learning uncertainty and shape priors.

Medical image analysis
The performance of deep learning for cardiac magnetic resonance imaging (MRI) segmentation is oftentimes degraded when using small datasets and sparse annotations for training or adapting a pre-trained model to previously unseen datasets. Here, we de...

Collaborative deep learning model for tooth segmentation and identification using panoramic radiographs.

Computers in biology and medicine
Panoramic radiographs are an integral part of effective dental treatment planning, supporting dentists in identifying impacted teeth, infections, malignancies, and other dental issues. However, screening for anomalies solely based on a dentist's asse...

Well Performance Classification and Prediction: Deep Learning and Machine Learning Long Term Regression Experiments on Oil, Gas, and Water Production.

Sensors (Basel, Switzerland)
In the oil and gas industries, predicting and classifying oil and gas production for hydrocarbon wells is difficult. Most oil and gas companies use reservoir simulation software to predict future oil and gas production and devise optimum field develo...