AIMC Topic: Neural Networks, Computer

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Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures.

Medical image analysis
The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineati...

Optimized artificial neural network based performance analysis of wheelchair movement for ALS patients.

Artificial intelligence in medicine
Individuals with neurodegenerative attacks loose the entire motor neuron movements. These conditions affect the individual actions like walking, speaking impairment and totally make the person in to locked in state (LIS). To overcome the miserable co...

Real-Time Visual Tracking with Variational Structure Attention Network.

Sensors (Basel, Switzerland)
Online training framework based on discriminative correlation filters for visual tracking has recently shown significant improvement in both accuracy and speed. However, correlation filter-base discriminative approaches have a common problem of track...

Adaptive-Cognitive Kalman Filter and Neural Network for an Upgraded Nondispersive Thermopile Device to Detect and Analyze Fusarium Spores.

Sensors (Basel, Switzerland)
Noises such as thermal noise, background noise or burst noise can reduce the reliability and confidence of measurement devices. In this work, a recursive and adaptive Kalman filter is proposed to detect and process burst noise or outliers and thermal...

SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.

NeuroImage. Clinical
White matter hyperintensities (WMHs) of presumed vascular origin are frequently observed in magnetic resonance images (MRIs) of the elderly. Detection and quantification of WMHs is important to help doctors make diagnoses and evaluate prognosis of th...

A novel bearing intelligent fault diagnosis framework under time-varying working conditions using recurrent neural network.

ISA transactions
Normal operation of bearing is the key to ensure the reliability and security of rotary machinery, so that bearing fault diagnosis is quite significant. However, the large amount of data collected by modern data acquisition system and time-varying wo...

Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks.

Medical image analysis
It remains challenging to automatically segment kidneys in clinical ultrasound (US) images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic methods have achieved promising performance. In this study, we pro...

Skin cancer diagnosis based on optimized convolutional neural network.

Artificial intelligence in medicine
Early detection of skin cancer is very important and can prevent some skin cancers, such as focal cell carcinoma and melanoma. Although there are several reasons that have bad impacts on the detection precision. Recently, the utilization of image pro...

Wearable Fall Detector Using Recurrent Neural Networks.

Sensors (Basel, Switzerland)
Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices allow the implementation of continuous and ubiquitous monitoring systems. The effectiveness for analy...

Comparison of Word Embeddings for Extraction from Medical Records.

International journal of environmental research and public health
This paper is an extension of the work originally presented in the 16th International Conference on Wearable, Micro and Nano Technologies for Personalized Health. Despite using electronic medical records, free narrative text is still widely used for ...