AIMC Topic: Deep Learning

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Deep Learning-Based Myoelectric Potential Estimation Method for Wheelchair Operation.

Sensors (Basel, Switzerland)
Wheelchair sports are recognized as an international sport, and research and support are being promoted to increase the competitiveness of wheelchair sports. For example, an electromyogram can observe muscle activity. However, it is generally used un...

The Challenge of Data Annotation in Deep Learning-A Case Study on Whole Plant Corn Silage.

Sensors (Basel, Switzerland)
Recent advances in computer vision are primarily driven by the usage of deep learning, which is known to require large amounts of data, and creating datasets for this purpose is not a trivial task. Larger benchmark datasets often have detailed proces...

PyUUL provides an interface between biological structures and deep learning algorithms.

Nature communications
Structural bioinformatics suffers from the lack of interfaces connecting biological structures and machine learning methods, making the application of modern neural network architectures impractical. This negatively affects the development of structu...

A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging.

Biomedical physics & engineering express
Over the past few years, positron emission tomography/computed tomography (PET/CT) imaging for computer-aided diagnosis has received increasing attention. Supervised deep learning architectures are usually employed for the detection of abnormalities,...

Deep learning-based extended field of view computed tomography image reconstruction: influence of network design on image estimation outside the scan field of view.

Biomedical physics & engineering express
The problem of data truncation in Computed Tomography (CT) is caused by the missing data when the patient exceeds the Scan Field of View (SFOV) of a CT scanner. The reconstruction of a truncated scan produces severe truncation artifacts both inside a...

Application of Deep Learning Technology in Glioma.

Journal of healthcare engineering
A common and most basic brain tumor is glioma that is exceptionally dangerous to health of various patients. A glioma segmentation, which is primarily magnetic resonance imaging (MRI) oriented, is considered as one of common tools developed for docto...

Pattern Recognition of Holographic Image Library Based on Deep Learning.

Journal of healthcare engineering
The final loss function in the deep learning neural network is composed of other functions in the network. Due to the existence of a large number of non-linear functions such as activation functions in the network, the entire deep learning model pres...

Application of Distributed Probability Model in Sports Based on Deep Learning: Deep Belief Network (DL-DBN) Algorithm for Human Behaviour Analysis.

Computational intelligence and neuroscience
With the increased development of information technology, almost all the sectors have been developed. Age, educational qualifications, gender, and other factors have no bearing on acquiring knowledge in information technology.Most humans use mobile p...

Application of the PBL Model Based on Deep Learning in Physical Education Classroom Integrating Production and Education.

Computational intelligence and neuroscience
This study aims to arouse students' interest in physical education (PE) in response to President Xi Jinping's call to strengthen students' physical quality because cultural courses occupy PE classes. Problem-based learning (PBL) is introduced, and a ...

Pea-KD: Parameter-efficient and accurate Knowledge Distillation on BERT.

PloS one
Knowledge Distillation (KD) is one of the widely known methods for model compression. In essence, KD trains a smaller student model based on a larger teacher model and tries to retain the teacher model's level of performance as much as possible. Howe...