AIMC Topic: Neural Networks, Computer

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MSTCN: A multiscale temporal convolutional network for user independent human activity recognition.

F1000Research
In recent years, human activity recognition (HAR) has been an active research topic due to its widespread application in various fields such as healthcare, sports, patient monitoring, etc. HAR approaches can be categorised as handcrafted feature met...

Cataract Disease Detection by Using Transfer Learning-Based Intelligent Methods.

Computational and mathematical methods in medicine
One of the most common visual disorders is cataracts, which people suffer from as they get older. The creation of a cloud on the lens of our eyes is known as a cataract. Blurred vision, faded colors, and difficulty seeing in strong light are the main...

LIO-CSI: LiDAR inertial odometry with loop closure combined with semantic information.

PloS one
Accurate and reliable state estimation and mapping are the foundation of most autonomous driving systems. In recent years, researchers have focused on pose estimation through geometric feature matching. However, most of the works in the literature as...

A localization strategy combined with transfer learning for image annotation.

PloS one
This study aims to solve the overfitting problem caused by insufficient labeled images in the automatic image annotation field. We propose a transfer learning model called CNN-2L that incorporates the label localization strategy described in this stu...

Convolutional Neural Network With Graphical Lasso to Extract Sparse Topological Features for Brain Disease Classification.

IEEE/ACM transactions on computational biology and bioinformatics
The functional connectivity provides new insights into the mechanisms of the human brain at network-level, which has been proved to be an effective biomarker for brain disease classification. Recently, machine learning methods have played an importan...

Identifying Microbe-Disease Association Based on a Novel Back-Propagation Neural Network Model.

IEEE/ACM transactions on computational biology and bioinformatics
Over the years, numerous evidences have demonstrated that microbes living in the human body are closely related to human life activities and human diseases. However, traditional biological experiments are time-consuming and expensive, so it has becom...

Multi-Label Classification Scheme Based on Local Regression for Retinal Vessel Segmentation.

IEEE/ACM transactions on computational biology and bioinformatics
Segmenting small retinal vessels with width less than 2 pixels in fundus images is a challenging task. In this paper, in order to effectively segment the vessels, especially the narrow parts, we propose a local regression scheme to enhance the narrow...

Drug-Target Interaction Prediction: End-to-End Deep Learning Approach.

IEEE/ACM transactions on computational biology and bioinformatics
The discovery of potential Drug-Target Interactions (DTIs) is a determining step in the drug discovery and repositioning process, as the effectiveness of the currently available antibiotic treatment is declining. Although putting efforts on the tradi...

A Memristive Circuit Implementation of Eyes State Detection in Fatigue Driving Based on Biological Long Short-Term Memory Rule.

IEEE/ACM transactions on computational biology and bioinformatics
Biological long short-term memory (B-LSTM) can effectively help human process all kinds of received information. In this work, a memristive B-LSTM circuit which mimics a conversion from short-term memory to long-term memory is proposed. That is, the ...

Using Convolutional Neural Networks to Measure the Physiological Age of Caenorhabditis elegans.

IEEE/ACM transactions on computational biology and bioinformatics
Caenorhabditis elegans (C. elegans) is a popular and excellent model for studies of aging due to its short lifespan. Methods for precisely measuring the physiological age of C. elegans are critically needed, especially for antiaging drug screening an...