AIMC Topic: Deep Learning

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Designing Deep Learning Hardware Accelerator and Efficiency Evaluation.

Computational intelligence and neuroscience
With the swift development of deep learning applications, the convolutional neural network (CNN) has brought a tremendous challenge to traditional processors to fulfil computing requirements. It is urgent to embrace new strategies to improve efficien...

Improvement of Speech Recognition Technology in Piano Music Scene Based on Deep Learning of Internet of Things.

Computational intelligence and neuroscience
The main goal of speech recognition technology is to use computers to convert human analog speech signals into computer-generated signals, such as behavior patterns or binary codes. Different from speaker identification and speaker confirmation, the ...

Optimization Algorithm of Urban Rail Transit Network Route Planning Using Deep Learning Technology.

Computational intelligence and neuroscience
Under the present background, optimizing the existing urban rail transit network is the focus of urban rail transit construction at present. Based on DL, this paper constructs the optimization algorithm of urban rail transit network route planning. A...

Deep Learning Dual Neural Networks in the Construction of Learning Models for Online Courses in Piano Education.

Computational intelligence and neuroscience
The use of deep learning (DL) and artificial intelligence (AI) in teaching children piano lessons promotes modern piano instruction and enhances the overall quality of education. To begin, a more thorough explanation of the teaching environment and t...

Unreferenced English articles' translation quality-oriented automatic evaluation technology using sparse autoencoder under the background of deep learning.

PloS one
Currently, both manual and automatic evaluation technology can evaluate the translation quality of unreferenced English articles, playing a particular role in detecting translation results. Still, their deficiency is the lack of a close or noticeable...

Deep learning applications in telerehabilitation speech therapy scenarios.

Computers in biology and medicine
Nowadays, many application scenarios benefit from automatic speech recognition (ASR) technology. Within the field of speech therapy, in some cases ASR is exploited in the treatment of dysarthria with the aim of supporting articulation output. However...

Automated detection of vascular remodeling in tumor-draining lymph nodes by the deep-learning tool HEV-finder.

The Journal of pathology
Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor-draining lymph nodes (TDLNs). Dilation of t...

Automated evaluation of rheumatoid arthritis from hand radiographs using Machine Learning and deep learning techniques.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The aim and objectives of the study are as follows: (i) to implement automated patch-based classification of hand X-ray images using modified pre-trained convolutional neural network (CNN) models; (ii) to develop a customized CNN model for automated ...

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications.

International journal of molecular sciences
All living organisms require metal ions for their energy production and metabolic and biosynthetic processes. Within cells, the metal ions involved in the formation of adducts interact with metabolites and macromolecules (proteins and nucleic acids)....

scDLC: a deep learning framework to classify large sample single-cell RNA-seq data.

BMC genomics
BACKGROUND: Using single-cell RNA sequencing (scRNA-seq) data to diagnose disease is an effective technique in medical research. Several statistical methods have been developed for the classification of RNA sequencing (RNA-seq) data, including, for e...