AIMC Topic: Deep Learning

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Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study.

European radiology
OBJECTIVES: To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an ...

Improving malicious email detection through novel designated deep-learning architectures utilizing entire email.

Neural networks : the official journal of the International Neural Network Society
In today's email dependent world, cyber criminals often target organizations using a variety of social engineering techniques and specially crafted malicious emails. When successful, such attacks can result in significant harm to physical and digital...

Biparametric prostate MRI: impact of a deep learning-based software and of quantitative ADC values on the inter-reader agreement of experienced and inexperienced readers.

La Radiologia medica
OBJECTIVE: To investigate the impact of an artificial intelligence (AI) software and quantitative ADC (qADC) on the inter-reader agreement, diagnostic performance, and reporting times of prostate biparametric MRI (bpMRI) for experienced and inexperie...

Application and Communication Optimization Technology of Unmanned Distribution Car under Deep Learning in Logistics Express of COVID-19.

Computational intelligence and neuroscience
This work aims to solve the problem that the daily necessities of urban residents cannot be delivered during coronavirus disease 2019 (COVID-19), thereby reducing the possibility of the delivery personnel contracting COVID-19 due to the need to trans...

SVision: a deep learning approach to resolve complex structural variants.

Nature methods
Complex structural variants (CSVs) encompass multiple breakpoints and are often missed or misinterpreted. We developed SVision, a deep-learning-based multi-object-recognition framework, to automatically detect and haracterize CSVs from long-read sequ...

PDC: Pearl Detection with a Counter Based on Deep Learning.

Sensors (Basel, Switzerland)
Pearl detection with a counter (PDC) in a noncontact and high-precision manner is a challenging task in the area of commercial production. Additionally, sea pearls are considered to be quite valuable, so the traditional manual counting methods are no...

Deep Learning Combined with Hyperspectral Imaging Technology for Variety Discrimination of .

Molecules (Basel, Switzerland)
Traditional Chinese herbal medicine (TCHM) plays an essential role in the international pharmaceutical industry due to its rich resources and unique curative properties. The flowers, stems, and leaves of Fritillaria contain a wide range of phytochemi...

A Hierarchical Ensemble Deep Learning Activity Recognition Approach with Wearable Sensors Based on Focal Loss.

International journal of environmental research and public health
Abnormal activity in daily life is a relatively common symptom of chronic diseases, such as dementia. There will probably be a variety of repetitive activities in dementia patients' daily life, such as repeated handling of objects and repeated packin...

Fast and accurate Ab Initio Protein structure prediction using deep learning potentials.

PLoS computational biology
Despite the immense progress recently witnessed in protein structure prediction, the modeling accuracy for proteins that lack sequence and/or structure homologs remains to be improved. We developed an open-source program, DeepFold, which integrates s...

Application of Deep Learning in College Physical Education Design under Flipped Classroom.

Computational intelligence and neuroscience
With the development of information technology, teaching reform has also undergone major changes. The traditional college physical education teaching method cannot meet the needs of the majority of students, and the physical education teaching mode c...