AIMC Topic: Neural Networks, Computer

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Data-dependent stability analysis of adversarial training.

Neural networks : the official journal of the International Neural Network Society
Stability analysis is an essential aspect of studying the generalization ability of deep learning, as it involves deriving generalization bounds for stochastic gradient descent-based training algorithms. Adversarial training is the most widely used d...

Going Smaller: Attention-based models for automated melanoma diagnosis.

Computers in biology and medicine
Computational approaches offer a valuable tool to aid with the early diagnosis of melanoma by increasing both the speed and accuracy of doctors' decisions. The latest and best-performing approaches often rely on large ensemble models, with the number...

Modelling the effect of base component properties and processing conditions on mixture products using probabilistic, knowledge-guided neural networks.

International journal of pharmaceutics
Development of materials by mixing different base components is a widespread methodology to create materials with improved properties compared to those of its base components. However, efficient determination of the properties of mixture-based materi...

Prediction of Brain Cancer Occurrence and Risk Assessment of Brain Hemorrhage Using Hybrid Deep Learning Technique.

Cancer investigation
The prediction of brain cancer occurrence and risk assessment of brain hemorrhage using a hybrid deep learning (DL) technique is a critical area of research in medical imaging analysis. One prominent challenge in this field is the accurate identifica...

Developmental Plasticity-Inspired Adaptive Pruning for Deep Spiking and Artificial Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
Developmental plasticity plays a prominent role in shaping the brain's structure during ongoing learning in response to dynamically changing environments. However, the existing network compression methods for deep artificial neural networks (ANNs) an...

A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma.

Environmental science & technology
Undocumented Orphaned Wells (UOWs) are wells without an operator that have limited or no documentation with regulatory authorities. An estimated 310,000 to 800,000 UOWs exist in the United States (US), whose locations are largely unknown. These wells...

Precision Thermostability Predictions: Leveraging Machine Learning for Examining Laccases and Their Associated Genes.

International journal of molecular sciences
Laccases, multi-copper oxidases, play pivotal roles in the oxidation of a variety of substrates, impacting numerous biological functions and industrial processes. However, their industrial adoption has been limited by challenges in thermostability. T...

Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis.

BMC musculoskeletal disorders
BACKGROUND: Osteoporosis is one of the most common metabolic diseases that is characterized by a decrease in bone density and a loss of the quality of the bone structure. The use of deep learning in the prediction of osteoporosis can provide a non-in...

Eeg based smart emotion recognition using meta heuristic optimization and hybrid deep learning techniques.

Scientific reports
In the domain of passive brain-computer interface applications, the identification of emotions is both essential and formidable. Significant research has recently been undertaken on emotion identification with electroencephalogram (EEG) data. The aim...

Revolutionizing healthcare: a comparative insight into deep learning's role in medical imaging.

Scientific reports
Recently, Deep Learning (DL) models have shown promising accuracy in analysis of medical images. Alzeheimer Disease (AD), a prevalent form of dementia, uses Magnetic Resonance Imaging (MRI) scans, which is then analysed via DL models. To address the ...