AIMC Topic: Neural Networks, Computer

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See-Through Vision With Unsupervised Scene Occlusion Reconstruction.

IEEE transactions on pattern analysis and machine intelligence
Among the greatest of the challenges of minimally invasive surgery (MIS) is the inadequate visualisation of the surgical field through keyhole incisions. Moreover, occlusions caused by instruments or bleeding can completely obfuscate anatomical landm...

Self-Supervised Video Representation Learning by Uncovering Spatio-Temporal Statistics.

IEEE transactions on pattern analysis and machine intelligence
This paper proposes a novel pretext task to address the self-supervised video representation learning problem. Specifically, given an unlabeled video clip, we compute a series of spatio-temporal statistical summaries, such as the spatial location and...

Graph Neural Networks With Convolutional ARMA Filters.

IEEE transactions on pattern analysis and machine intelligence
Popular graph neural networks implement convolution operations on graphs based on polynomial spectral filters. In this paper, we propose a novel graph convolutional layer inspired by the auto-regressive moving average (ARMA) filter that, compared to ...

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size.

IEEE transactions on pattern analysis and machine intelligence
Neural architecture search (NAS) has attracted a lot of attention and has been illustrated to bring tangible benefits in a large number of applications in the past few years. Architecture topology and architecture size have been regarded as two of th...

Convolutional Neural Networks With Gated Recurrent Connections.

IEEE transactions on pattern analysis and machine intelligence
The convolutional neural network (CNN) has become a basic model for solving many computer vision problems. In recent years, a new class of CNNs, recurrent convolution neural network (RCNN), inspired by abundant recurrent connections in the visual sys...

Surface Wettability Prediction Using Image Analysis and an Artificial Neural Network.

Langmuir : the ACS journal of surfaces and colloids
In this study, a wettability-predicting method that uses an artificial neural network (ANN) by learning from digital images of the actual surface structures was developed. Polyester film surfaces were treated with oxygen plasma to realize various nan...

Empirical analyses and simulations showed that different machine and statistical learning methods had differing performance for predicting blood pressure.

Scientific reports
Machine learning is increasingly being used to predict clinical outcomes. Most comparisons of different methods have been based on empirical analyses in specific datasets. We used Monte Carlo simulations to determine when machine learning methods per...

Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing.

Nature communications
Neuromorphic computing, a computing paradigm inspired by the human brain, enables energy-efficient and fast artificial neural networks. To process information, neuromorphic computing directly mimics the operation of biological neurons in a human brai...

A new active learning approach for adsorbate-substrate structural elucidation in silico.

Journal of molecular modeling
Adsorbate interactions with substrates (e.g. surfaces and nanoparticles) are fundamental for several technologies, such as functional materials, supramolecular chemistry, and solvent interactions. However, modeling these kinds of systems in silico, s...

Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent.

IEEE journal of biomedical and health informatics
Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating. Nowadays, enhancement on medical diagnosis via machine learning models has been highly effective in many aspects of e-health analy...