AIMC Topic: Neural Networks, Computer

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The inhibitory effect of functional lesions on eloquent brain areas: from research bench to operating bed.

The International journal of neuroscience
Functioning, but injured cerebral connections are hypothesized to inhibit cortical plasticity. Study of neural networks can validate this hypothesis, and provide further practical clues for clinical and surgical options to restore function in eloque...

Artificial intelligence weights the importance of factors predicting complete cytoreduction at secondary cytoreductive surgery for recurrent ovarian cancer.

Journal of gynecologic oncology
OBJECTIVE: Accumulating evidence support that complete cytoreduction (CC) at the time of secondary cytoreductive surgery (SCS) improves survival in patients affected by recurrent ovarian cancer (ROC). Here, we aimed to determine whether artificial in...

3D Randomized Connection Network with Graph-based Label Inference.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, a novel 3D deep learning network is proposed for brain MR image segmentation with randomized connection, which can decrease the dependency between layers and increase the network capacity. The convolutional LSTM and 3D convolution are ...

Quasi-projective synchronization of fractional-order complex-valued recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, without separating the complex-valued neural networks into two real-valued systems, the quasi-projective synchronization of fractional-order complex-valued neural networks is investigated. First, two new fractional-order inequalities a...

VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography.

Medical image analysis
Three-dimensional (3D) fetal neurosonography is used clinically to detect cerebral abnormalities and to assess growth in the developing brain. However, manual identification of key brain structures in 3D ultrasound images requires expertise to perfor...

Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.

Journal of medical systems
In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network (CNN). A CNN model was designed with six optimized convolution layers incl...

Computational mechanisms underlying cortical responses to the affordance properties of visual scenes.

PLoS computational biology
Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and...

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decreased. Five important river water quality properties such as: dissolved oxygen (DO), total dissolved sol...

Generalized pinning synchronization of delayed Cohen-Grossberg neural networks with discontinuous activations.

Neural networks : the official journal of the International Neural Network Society
In this article, generalized pinning synchronization problem is investigated for a class of Cohen-Grossberg neural networks with discontinuous neuron activations and mixed delays. By designing generalized pinning state-feedback and adaptive controlle...

Hedging Deep Features for Visual Tracking.

IEEE transactions on pattern analysis and machine intelligence
Convolutional Neural Networks (CNNs) have been applied to visual tracking with demonstrated success in recent years. Most CNN-based trackers utilize hierarchical features extracted from a certain layer to represent the target. However, features from ...