AIMC Topic: Neural Networks, Computer

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Improvement of Lightweight Convolutional Neural Network Model Based on YOLO Algorithm and Its Research in Pavement Defect Detection.

Sensors (Basel, Switzerland)
To ensure the safe operation of highway traffic lines, given the imperfect feature extraction of existing road pit defect detection models and the practicability of detection equipment, this paper proposes a lightweight target detection algorithm wit...

Split BiRNN for real-time activity recognition using radar and deep learning.

Scientific reports
Radar systems can be used to perform human activity recognition in a privacy preserving manner. This can be achieved by using Deep Neural Networks, which are able to effectively process the complex radar data. Often these networks are large and do no...

iProm-Zea: A two-layer model to identify plant promoters and their types using convolutional neural network.

Genomics
A promoter is a short DNA sequence near the start codon, responsible for initiating the transcription of a specific gene in the genome. The accurate recognition of promoters is important for achieving a better understanding of transcriptional regulat...

Detecting and Extracting Brain Hemorrhages from CT Images Using Generative Convolutional Imaging Scheme.

Computational intelligence and neuroscience
PURPOSE: The need for computerized medical assistance for accurate detection of brain hemorrhage from Computer Tomography (CT) images is more mandatory than conventional clinical tests. Recent technologies and advanced computerized algorithms follow ...

Evaluation of Smart City Sustainable Development Prospects Based on Fuzzy Comprehensive Evaluation Method.

Computational intelligence and neuroscience
In this study, the method of a fuzzy comprehensive evaluation is used to analyze the research situation of smart city development, and 20 evaluation indicator systems are selected as the original indicator database; the relevant sustainable developme...

The Blockchain Technology Applied in the Development of Real Economy in Jiangsu under Deep Learning.

Computational intelligence and neuroscience
This study focuses on the financing difficulties of small and medium enterprises (SMEs) in China to study the application of blockchain technology in developing the real economy. Deep learning neural network is applied to the vulnerability analysis a...

A deep learning framework for enhancer prediction using word embedding and sequence generation.

Biophysical chemistry
Enhancers are non-coding DAN fragments that play key roles in gene regulations and can promote the transcription of structural genes, thereby affecting the expression of structural protein catalytic enzymes and regulatory proteins. Accurate identific...

Exploiting exercise electrocardiography to improve early diagnosis of atrial fibrillation with deep learning neural networks.

Computers in biology and medicine
Atrial fibrillation (AF) is the most common type of sustained arrhythmia. It results from abnormal irregularities in the electrical performance of the atria, and may cause heart thrombosis, stroke, arterial disease, thromboembolism, and heart failure...

Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks.

IEEE transactions on pattern analysis and machine intelligence
Deep neural models, in recent years, have been successful in almost every field, even solving the most complex problem statements. However, these models are huge in size with millions (and even billions) of parameters, demanding heavy computation pow...

Deep Learning for Person Re-Identification: A Survey and Outlook.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increa...