AIMC Topic: Neural Networks, Computer

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Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (...

Characterization of the stimulus waveforms generated by implantable pulse generators for deep brain stimulation.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To determine the circuit elements required to theoretically describe the stimulus waveforms generated by an implantable pulse generator (IPG) during clinical deep brain stimulation (DBS).

Coupled generative adversarial stacked Auto-encoder: CoGASA.

Neural networks : the official journal of the International Neural Network Society
Coupled Generative Adversarial Network (CoGAN) was recently introduced in order to model a joint distribution of a multi modal dataset. The CoGAN model lacks the capability to handle noisy data as well as it is computationally expensive and inefficie...

O(t)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

Neural networks : the official journal of the International Neural Network Society
This paper investigates O(t)-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and di...

Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods.

Neural networks : the official journal of the International Neural Network Society
This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Con...

A novel type of activation function in artificial neural networks: Trained activation function.

Neural networks : the official journal of the International Neural Network Society
Determining optimal activation function in artificial neural networks is an important issue because it is directly linked with obtained success rates. But, unfortunately, there is not any way to determine them analytically, optimal activation functio...

Assessment of cortical bone fracture resistance curves by fusing artificial neural networks and linear regression.

Computer methods in biomechanics and biomedical engineering
Bone injures (BI) represents one of the major health problems, together with cancer and cardiovascular diseases. Assessment of the risks associated with BI is nontrivial since fragility of human cortical bone is varying with age. Due to restrictions ...

Respiratory motion correction for free-breathing 3D abdominal MRI using CNN-based image registration: a feasibility study.

The British journal of radiology
OBJECTIVE: Free-breathing abdomen imaging requires non-rigid motion registration of unavoidable respiratory motion in three-dimensional undersampled data sets. In this work, we introduce an image registration method based on the convolutional neural ...

Early prediction of cognitive deficits in very preterm infants using functional connectome data in an artificial neural network framework.

NeuroImage. Clinical
Investigation of the brain's functional connectome can improve our understanding of how an individual brain's organizational changes influence cognitive function and could result in improved individual risk stratification. Brain connectome studies in...