AIMC Topic: Neural Networks, Computer

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A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification.

International journal of molecular sciences
Essential genes contain key information of genomes that could be the key to a comprehensive understanding of life and evolution. Because of their importance, studies of essential genes have been considered a crucial problem in computational biology. ...

Conditional Generative Adversarial Networks Aided Motion Correction of Dynamic F-FDG PET Brain Studies.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
This work set out to develop a motion-correction approach aided by conditional generative adversarial network (cGAN) methodology that allows reliable, data-driven determination of involuntary subject motion during dynamic F-FDG brain studies. Ten he...

Mitigation of ocular artifacts for EEG signal using improved earth worm optimization-based neural network and lifting wavelet transform.

Computer methods in biomechanics and biomedical engineering
An Electroencephalogram (EEG) is often tarnished by various categories of artifacts. Numerous efforts have been taken to improve its quality by eliminating the artifacts. The EEG involves the biological artifacts (ocular artifacts, ECG and EMG artifa...

Approximation rates for neural networks with encodable weights in smoothness spaces.

Neural networks : the official journal of the International Neural Network Society
We examine the necessary and sufficient complexity of neural networks to approximate functions from different smoothness spaces under the restriction of encodable network weights. Based on an entropy argument, we start by proving lower bounds for the...

Generating photo-realistic training data to improve face recognition accuracy.

Neural networks : the official journal of the International Neural Network Society
Face recognition has become a widely adopted biometric in forensics, security and law enforcement thanks to the high accuracy achieved by systems based on convolutional neural networks (CNNs). However, to achieve good performance, CNNs need to be tra...

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...

Machine learning techniques for mitoses classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: Pathologists analyze biopsy material at both the cellular and structural level to determine diagnosis and cancer stage. Mitotic figures are surrogate biomarkers of cellular proliferation that can provide prognostic information; thus, thei...

Spatial feature fusion convolutional network for liver and liver tumor segmentation from CT images.

Medical physics
PURPOSE: The accurate segmentation of liver and liver tumors from CT images can assist radiologists in decision-making and treatment planning. The contours of liver and liver tumors are currently obtained by manual labeling, which is time-consuming a...

Adding Stochastic Negative Examples into Machine Learning Improves Molecular Bioactivity Prediction.

Journal of chemical information and modeling
Multitask deep neural networks learn to predict ligand-target binding by example, yet public pharmacological data sets are sparse, imbalanced, and approximate. We constructed two hold-out benchmarks to approximate temporal and drug-screening test sce...

Bidirectional Attention for Text-Dependent Speaker Verification.

Sensors (Basel, Switzerland)
Automatic speaker verification provides a flexible and effective way for biometric authentication. Previous deep learning-based methods have demonstrated promising results, whereas a few problems still require better solutions. In prior works examini...