AIMC Topic: Neural Networks, Computer

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Multifrequency Hebbian plasticity in coupled neural oscillators.

Biological cybernetics
We study multifrequency Hebbian plasticity by analyzing phenomenological models of weakly connected neural networks. We start with an analysis of a model for single-frequency networks previously shown to learn and memorize phase differences between c...

Mask R-CNN and OBIA Fusion Improves the Segmentation of Scattered Vegetation in Very High-Resolution Optical Sensors.

Sensors (Basel, Switzerland)
Vegetation generally appears scattered in drylands. Its structure, composition and spatial patterns are key controls of biotic interactions, water, and nutrient cycles. Applying segmentation methods to very high-resolution images for monitoring chang...

iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network.

Computational and mathematical methods in medicine
A promoter is a short DNA sequence near to the start codon, responsible for initiating transcription of a specific gene in genome. The accurate recognition of promoters has great significance for a better understanding of the transcriptional regulati...

Deep Ensemble Feature Network for Gastric Section Classification.

IEEE journal of biomedical and health informatics
In this paper, we propose a novel deep ensemble feature (DEF) network to classify gastric sections from endoscopic images. Different from recent deep ensemble learning methods, which need to train deep features and classifiers individually to obtain ...

Learning Spatiotemporal Features for Esophageal Abnormality Detection From Endoscopic Videos.

IEEE journal of biomedical and health informatics
Esophageal cancer is categorized as a type of disease with a high mortality rate. Early detection of esophageal abnormalities (i.e. precancerous and early cancerous) can improve the survival rate of the patients. Recent deep learning-based methods fo...

Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses.

IEEE journal of biomedical and health informatics
The prospective identification of children likely to develop schizophrenia is a vital tool to support early interventions that can mitigate the risk of progression to clinical psychosis. Electroencephalographic (EEG) patterns from brain activity and ...

Multi-Scale Self-Guided Attention for Medical Image Segmentation.

IEEE journal of biomedical and health informatics
Even though convolutional neural networks (CNNs) are driving progress in medical image segmentation, standard models still have some drawbacks. First, the use of multi-scale approaches, i.e., encoder-decoder architectures, leads to a redundant use of...

RippleNet: a Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection.

Neuroinformatics
Hippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. Understanding their underlying mechanisms in healthy and pathological brain function and beh...

Steganographer detection via a similarity accumulation graph convolutional network.

Neural networks : the official journal of the International Neural Network Society
Steganographer detection aims to identify guilty users who conceal secret information in a number of images for the purpose of covert communication in social networks. Existing steganographer detection methods focus on designing discriminative featur...

GA-based implicit stochastic optimization and RNN-based simulation for deriving multi-objective reservoir hedging rules.

Environmental science and pollution research international
Management of reservoir systems is a complicated process involving many uncertainties regarding future events and the diversity of purposes these reservoirs serve; therefore, an effective management of these systems could help improve resource utiliz...