AIMC Topic: Neural Networks, Computer

Clear Filters Showing 22801 to 22810 of 31376 articles

KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks.

Computational intelligence and neuroscience
Keratoconus (KTC) is a noninflammatory disorder characterized by progressive thinning, corneal deformation, and scarring of the cornea. The pathological mechanisms of this condition have been investigated for a long time. In recent years, this diseas...

Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation.

IEEE transactions on pattern analysis and machine intelligence
We investigate two crucial and closely-related aspects of CNNs for optical flow estimation: models and training. First, we design a compact but effective CNN model, called PWC-Net, according to simple and well-established principles: pyramidal proces...

Early esophageal adenocarcinoma detection using deep learning methods.

International journal of computer assisted radiology and surgery
PURPOSE: This study aims to adapt and evaluate the performance of different state-of-the-art deep learning object detection methods to automatically identify esophageal adenocarcinoma (EAC) regions from high-definition white light endoscopy (HD-WLE) ...

Deep Convolutional Neural Networks for Heart Sound Segmentation.

IEEE journal of biomedical and health informatics
This paper studies the use of deep convolutional neural networks to segment heart sounds into their main components. The proposed methods are based on the adoption of a deep convolutional neural network architecture, which is inspired by similar appr...

Attention Residual Learning for Skin Lesion Classification.

IEEE transactions on medical imaging
Automated skin lesion classification in dermoscopy images is an essential way to improve the diagnostic performance and reduce melanoma deaths. Although deep convolutional neural networks (DCNNs) have made dramatic breakthroughs in many image classif...

Liver Extraction Using Residual Convolution Neural Networks From Low-Dose CT Images.

IEEE transactions on bio-medical engineering
An efficient and precise liver extraction from computed tomography (CT) images is a crucial step for computer-aided hepatic diseases diagnosis and treatment. Considering the possible risk to patient's health due to X-ray radiation of repetitive CT ex...

Incorporation of a spectral model in a convolutional neural network for accelerated spectral fitting.

Magnetic resonance in medicine
PURPOSE: MRSI has shown great promise in the detection and monitoring of neurologic pathologies such as tumor. A necessary component of data processing includes the quantitation of each metabolite, typically done through fitting a model of the spectr...

Network structure and input integration in competing firing rate models for decision-making.

Journal of computational neuroscience
Making a decision among numerous alternatives is a pervasive and central undertaking encountered by mammals in natural settings. While decision making for two-option tasks has been studied extensively both experimentally and theoretically, characteri...

Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals.

Computers in biology and medicine
Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in neurological and clinical studies. NCP represents the mental/cognitive human capacity in performing a specific task. It is difficult to develop the study prot...