AIMC Topic: Neural Networks, Computer

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BooDet: Gradient Boosting Object Detection With Additive Learning-Based Prediction Aggregation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In recent years, the community of object detection has witnessed remarkable progress with the development of deep neural networks. But the detection performance still suffers from the dilemma between complex networks and single-vector predictions. In...

Subcortical segmentation of the fetal brain in 3D ultrasound using deep learning.

NeuroImage
The quantification of subcortical volume development from 3D fetal ultrasound can provide important diagnostic information during pregnancy monitoring. However, manual segmentation of subcortical structures in ultrasound volumes is time-consuming and...

Image quality assessment for machine learning tasks using meta-reinforcement learning.

Medical image analysis
In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is performed using machine learning algorithms, such as a neural-network-bas...

An end-to-end computer vision methodology for quantitative metallography.

Scientific reports
Metallography is crucial for a proper assessment of material properties. It mainly involves investigating the spatial distribution of grains and the occurrence and characteristics of inclusions or precipitates. This work presents a holistic few-shot ...

EDNC: Ensemble Deep Neural Network for COVID-19 Recognition.

Tomography (Ann Arbor, Mich.)
The automatic recognition of COVID-19 diseases is critical in the present pandemic since it relieves healthcare staff of the burden of screening for infection with COVID-19. Previous studies have proven that deep learning algorithms can be utilized t...

Learning-based occupational x-ray scatter estimation.

Physics in medicine and biology
During x-ray-guided interventional procedures, the medical staff is exposed to scattered ionizing radiation caused by the patient. To increase the staff's awareness of the invisible radiation and monitor dose online, computational scatter estimation ...

TSGB: Target-Selective Gradient Backprop for Probing CNN Visual Saliency.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The explanation for deep neural networks has drawn extensive attention in the deep learning community over the past few years. In this work, we study the visual saliency, a.k.a. visual explanation, to interpret convolutional neural networks. Compared...

Lower-Limb Joint Torque Prediction Using LSTM Neural Networks and Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Estimation of joint torque during movement provides important information in several settings, such as effect of athletes' training or of a medical intervention, or analysis of the remaining muscle strength in a wearer of an assistive device. The abi...

Investigation of the Temperature Compensation of Piezoelectric Weigh-In-Motion Sensors Using a Machine Learning Approach.

Sensors (Basel, Switzerland)
Piezoelectric ceramics have good electromechanical coupling characteristics and a high sensitivity to load. One typical engineering application of piezoelectric ceramic is its use as a signal source for Weigh-In-Motion (WIM) systems in road traffic m...