AIMC Topic: Neural Networks, Computer

Clear Filters Showing 28681 to 28690 of 31376 articles

Successes and challenges in using machine-learned activation energies in kinetic simulations.

The Journal of chemical physics
The prediction of the thermodynamic and kinetic properties of chemical reactions is increasingly being addressed by machine-learning (ML) methods, such as artificial neural networks (ANNs). While a number of recent studies have reported success in pr...

Convolutional neural network-based common-path optical coherence tomography A-scan boundary-tracking training and validation using a parallel Monte Carlo synthetic dataset.

Optics express
We present a parallel Monte Carlo (MC) simulation platform for rapidly generating synthetic common-path optical coherence tomography (CP-OCT) A-scan image dataset for image-guided needle insertion. The computation time of the method has been evaluate...

Experimental implementation of spike-based neuromorphic XOR operation based on polarization-mode competition in a single VCSOA.

Applied optics
We experimentally and numerically propose an approach for implementing spike-based neuromorphic exclusive OR (XOR) operation using a single vertical-cavity semiconductor optical amplifier (VCSOA). XOR operation is realized based on the neuron-like in...

Stair Recognition for Robotic Exoskeleton Control using Computer Vision and Deep Learning.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Computer vision can be used in robotic exoskeleton control to improve transitions between different locomotion modes through the prediction of future environmental states. Here we present the development of a large-scale automated stair recognition s...

Predictive Analysis of Errors During Robot-Mediated Gamified Training.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
This paper presents our approach to predicting future error-related events in a robot-mediated gamified physical training activity for stroke patients. The ability to predict future error under such conditions suggests the existence of distinguishabl...

Comparison of Machine Learning Techniques for Activities of Daily Living Classification with Electromyographic Data.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Advances in data science and wearable robotic devices present an opportunity to improve rehabilitation outcomes. Some of these devices incorporate electromyography (EMG) electrodes that sense physiological patient activity, making it possible to deve...

Generative Moment Matching Networks for Genotype Simulation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The generation of synthetic genomic sequences using neural networks has potential to ameliorate privacy and data sharing concerns and to mitigate potential bias within datasets due to under-representation of some population groups. However, there is ...

Multi-Expert Deep Networks for Multi-Disease Detection in Retinal Fundus Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic diagnosis of eye diseases from retinal fundus images is quite challenging. Common public datasets include images of subjects with multiple diseases with uneven distribution of labels. Rare diseases are especially challenging due to their un...

Hospital-Agnostic Image Representation Learning in Digital Pathology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference in procedures to acquire WSIs at various trial sites gives rise to variability in the histopathology images, thus making consistent diagnosis challeng...

Rethinking ImageNet Pre-training for Computational Histopathology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Transfer learning from ImageNet pretrained weights is widely used when training Deep Learning models on a Histopathology dataset. However, the visual features of the two domains are different. Rather than ImageNet pretrained weights, pre-training on ...