AIMC Topic: Neural Networks, Computer

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Efficient and Stable Graph Scattering Transforms via Pruning.

IEEE transactions on pattern analysis and machine intelligence
Graph convolutional networks (GCNs) have well-documented performance in various graph learning tasks, but their analysis is still at its infancy. Graph scattering transforms (GSTs) offer training-free deep GCN models that extract features from graph ...

Semantic Object Accuracy for Generative Text-to-Image Synthesis.

IEEE transactions on pattern analysis and machine intelligence
Generative adversarial networks conditioned on textual image descriptions are capable of generating realistic-looking images. However, current methods still struggle to generate images based on complex image captions from a heterogeneous domain. Furt...

Building and Interpreting Deep Similarity Models.

IEEE transactions on pattern analysis and machine intelligence
Many learning algorithms such as kernel machines, nearest neighbors, clustering, or anomaly detection, are based on distances or similarities. Before similarities are used for training an actual machine learning model, we would like to verify that th...

Meta-Transfer Learning Through Hard Tasks.

IEEE transactions on pattern analysis and machine intelligence
Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few...

A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences.

International journal of molecular sciences
As one of the most important post-translational modifications (PTMs), phosphorylation refers to the binding of a phosphate group with amino acid residues like Ser (S), Thr (T) and Tyr (Y) thus resulting in diverse functions at the molecular level. Ab...

Implementation of Sequence-Based Classification Methods for Motion Assessment and Recognition in a Traditional Chinese Sport (Baduanjin).

International journal of environmental research and public health
This study aimed to assess the motion accuracy of Baduanjin and recognise the motions of Baduanjin based on sequence-based methods. Motion data of Baduanjin were measured by the inertial sensor measurement system (IMU). Fifty-four participants were r...

A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes.

Sensors (Basel, Switzerland)
In order to develop a non-contact and simple gesture recognition technology, a recognition method with a charge induction array of nine electrodes is proposed. Firstly, the principle of signal acquisition based on charge induction is introduced, and ...

Classification and Explanation for Intrusion Detection System Based on Ensemble Trees and SHAP Method.

Sensors (Basel, Switzerland)
In recent years, many methods for intrusion detection systems (IDS) have been designed and developed in the research community, which have achieved a perfect detection rate using IDS datasets. Deep neural networks (DNNs) are representative examples a...

Modelling the reference crop evapotranspiration in the Beas-Sutlej basin (India): an artificial neural network approach based on different combinations of meteorological data.

Environmental monitoring and assessment
Accurate prediction of the reference evapotranspiration (ET) is vital for estimating the crop water requirements precisely. In this study, we developed multi-layer perceptron artificial neural network (MLP-ANN) models considering different combinatio...