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Pattern Recognition, Automated

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Greedy auto-augmentation for n-shot learning using deep neural networks.

Neural networks : the official journal of the International Neural Network Society
The goal of n-shot learning is the classification of input data from small datasets. This type of learning is challenging in neural networks, which typically need a high number of data during the training process. Recent advancements in data augmenta...

A Data-Driven Approach to Predict and Classify Epileptic Seizures from Brain-Wide Calcium Imaging Video Data.

IEEE/ACM transactions on computational biology and bioinformatics
The prediction of epileptic seizures has been an essential problem of epilepsy study. The calcium imaging video data images the whole brain-wide neurons activities with electrical discharge recorded by calcium fluorescence intensity (CFI). In this pa...

DAPath: Distance-aware knowledge graph reasoning based on deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Knowledge graph reasoning aims to find reasoning paths for relations over incomplete knowledge graphs (KG). Prior works may not take into account that the rewards for each position (vertex in the graph) may be different. We propose the distance-aware...

Joint Person Objectness and Repulsion for Person Search.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person search targets to search the probe person from the unconstrainted scene images, which can be treated as the combination of person detection and person matching. However, the existing methods based on the Detection-Matching framework ignore the...

Stacking-Based Deep Neural Network: Deep Analytic Network for Pattern Classification.

IEEE transactions on cybernetics
Stacking-based deep neural network (S-DNN) is aggregated with pluralities of basic learning modules, one after another, to synthesize a deep neural network (DNN) alternative for pattern classification. Contrary to the DNNs trained from end to end by ...

Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons.

IEEE transactions on neural networks and learning systems
This article proposes an unsupervised address event representation (AER) object recognition approach. The proposed approach consists of a novel multiscale spatio-temporal feature (MuST) representation of input AER events and a spiking neural network ...

A brain-inspired network architecture for cost-efficient object recognition in shallow hierarchical neural networks.

Neural networks : the official journal of the International Neural Network Society
The brain successfully performs visual object recognition with a limited number of hierarchical networks that are much shallower than artificial deep neural networks (DNNs) that perform similar tasks. Here, we show that long-range horizontal connecti...

Necessary conditions for STDP-based pattern recognition learning in a memristive spiking neural network.

Neural networks : the official journal of the International Neural Network Society
This work is aimed to study experimental and theoretical approaches for searching effective local training rules for unsupervised pattern recognition by high-performance memristor-based Spiking Neural Networks (SNNs). First, the possibility of weight...

Facial Expression Recognition Using Frequency Neural Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Facial expression recognition has become a newly-emerging topic in recent decades, which has important value in the field of human-computer interaction. In this paper, we present a deep learning based approach, named frequency neural network (FreNet)...