AIMC Topic: Neural Networks, Computer

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A classification-based approach to semi-supervised clustering with pairwise constraints.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce a neural network framework for semi-supervised clustering with pairwise (must-link or cannot-link) constraints. In contrast to existing approaches, we decompose semi-supervised clustering into two simpler classification ta...

DART: Domain-Adversarial Residual-Transfer networks for unsupervised cross-domain image classification.

Neural networks : the official journal of the International Neural Network Society
The accuracy of deep learning (e.g., convolutional neural networks) for an image classification task critically relies on the amount of labeled training data. Aiming to solve an image classification task on a new domain that lacks labeled data but ga...

Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction.

Journal of chemical information and modeling
Advances in deep neural network (DNN)-based molecular property prediction have recently led to the development of models of remarkable accuracy and generalization ability, with graph convolutional neural networks (GCNNs) reporting state-of-the-art pe...

Shedding Light on People Action Recognition in Social Robotics by Means of Common Spatial Patterns.

Sensors (Basel, Switzerland)
Action recognition in robotics is a research field that has gained momentum in recent years. In this work, a video activity recognition method is presented, which has the ultimate goal of endowing a robot with action recognition capabilities for a mo...

Birds have peramorphic skulls, too: anatomical network analyses reveal oppositional heterochronies in avian skull evolution.

Communications biology
In contrast to the vast majority of reptiles, the skulls of adult crown birds are characterized by a high degree of integration due to bone fusion, e.g., an ontogenetic event generating a net reduction in the number of bones. To understand this proce...

Automating in vivo cardiac diffusion tensor postprocessing with deep learning-based segmentation.

Magnetic resonance in medicine
PURPOSE: In this work we develop and validate a fully automated postprocessing framework for in vivo diffusion tensor cardiac magnetic resonance (DT-CMR) data powered by deep learning.

Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability Domain .

Journal of chemical information and modeling
In ligand-based virtual screening, high-throughput screening (HTS) data sets can be exploited to train classification models. Such models can be used to prioritize yet untested molecules, from the most likely active (against a protein target of inter...

Discrimination of Tetrastigma hemsleyanum according to geographical origin by near-infrared spectroscopy combined with a deep learning approach.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Recently, deep learning has presented as a powerful approach to overcome the deficiencies of the conventional biochemical approaches. In this study, a method for discriminating medicinal plant Tetrastigma hemsleyanum from different origins was propos...

Artificial intelligence for early prediction of pulmonary hypertension using electrocardiography.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
BACKGROUND: Screening and early diagnosis of pulmonary hypertension (PH) are critical for managing progression and preventing associated mortality; however, there are no tools for this purpose. We developed and validated an artificial intelligence (A...

Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis.

Medical image analysis
Functional connectivity networks (FCNs) based on functional magnetic resonance imaging (fMRI) have been widely applied to analyzing and diagnosing brain diseases, such as Alzheimer's disease (AD) and its prodrome stage, i.e., mild cognitive impairmen...