AIMC Topic: Neural Networks, Computer

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Fully automatic segmentation of glottis and vocal folds in endoscopic laryngeal high-speed videos using a deep Convolutional LSTM Network.

PloS one
The objective investigation of the dynamic properties of vocal fold vibrations demands the recording and further quantitative analysis of laryngeal high-speed video (HSV). Quantification of the vocal fold vibration patterns requires as a first step t...

DMENet: Diabetic Macular Edema diagnosis using Hierarchical Ensemble of CNNs.

PloS one
UNLABELLED: Diabetic Macular Edema (DME) is an advanced stage of Diabetic Retinopathy (DR) and can lead to permanent vision loss. Currently, it affects 26.7 million people globally and on account of such a huge number of DME cases and the limited num...

Reconstruction of natural visual scenes from neural spikes with deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreover, it is also a cornerstone for designing algorithms of brain-machine interface, where decoding inco...

Using Harmony Search Algorithm in Neural Networks to Improve Fraud Detection in Banking System.

Computational intelligence and neuroscience
Financial fraud is among the main problems undermining the confidence of customers in addition to incurring economic losses to banks and financial institutions. In recent years, along with the proliferation of fraud, financial institutions began look...

Segmenting skin ulcers and measuring the wound area using deep convolutional networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Bedridden patients presenting chronic skin ulcers often need to be examined at home. Healthcare professionals follow the evolution of the patients' condition by regularly taking pictures of the wounds, as different aspects ...

Multi-task learning for the segmentation of organs at risk with label dependence.

Medical image analysis
Automatic segmentation of organs at risk is crucial to aid diagnoses and remains a challenging task in medical image analysis domain. To perform the segmentation, we use multi-task learning (MTL) to accurately determine the contour of organs at risk ...

Image Based Liver Toxicity Prediction.

Journal of chemical information and modeling
The drugs we use to cure our diseases can cause damage to the liver as it is the primary organ responsible for metabolism of environmental chemicals and drugs. To identify and eliminate potentially problematic drug candidates in the early stages of d...

Event-triggered synchronization of discrete-time neural networks: A switching approach.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the event-triggered synchronization control of discrete-time neural networks. The main highlights are threefold: (1) a new event-triggered mechanism (ETM) is presented, which can be regarded as a switching between the discrete...

Modeling uncertainty-seeking behavior mediated by cholinergic influence on dopamine.

Neural networks : the official journal of the International Neural Network Society
Recent findings suggest that acetylcholine mediates uncertainty-seeking behaviors through its projection to dopamine neurons - another neuromodulatory system known for its major role in reinforcement learning and decision-making. In this paper, we pr...