AIMC Topic: Neural Networks, Computer

Clear Filters Showing 24581 to 24590 of 31376 articles

Photorealistic Monocular Gaze Redirection Using Machine Learning.

IEEE transactions on pattern analysis and machine intelligence
We propose a general approach to the gaze redirection problem in images that utilizes machine learning. The idea is to learn to re-synthesize images by training on pairs of images with known disparities between gaze directions. We show that such lear...

A New Method for Automatic Sleep Stage Classification.

IEEE transactions on biomedical circuits and systems
Traditionally, automatic sleep stage classification is quite a challenging task because of the difficulty in translating open-textured standards to mathematical models and the limitations of handcrafted features. In this paper, a new system for autom...

On Multiple AER Handshaking Channels Over High-Speed Bit-Serial Bidirectional LVDS Links With Flow-Control and Clock-Correction on Commercial FPGAs for Scalable Neuromorphic Systems.

IEEE transactions on biomedical circuits and systems
Address event representation (AER) is a widely employed asynchronous technique for interchanging "neural spikes" between different hardware elements in neuromorphic systems. Each neuron or cell in a chip or a system is assigned an address (or ID), wh...

A Grey Wolf Optimizer for Modular Granular Neural Networks for Human Recognition.

Computational intelligence and neuroscience
A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its e...

A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.

Medical physics
BACKGROUND: Deep learning methods for radiomics/computer-aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for extensive image preprocessing.

Faceness-Net: Face Detection through Deep Facial Part Responses.

IEEE transactions on pattern analysis and machine intelligence
We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision. We observe a phenomenon that part detectors emerge within CNN trained to classify attributes from uncropped face images, withou...

"What is relevant in a text document?": An interpretable machine learning approach.

PloS one
Text documents can be described by a number of abstract concepts such as semantic category, writing style, or sentiment. Machine learning (ML) models have been trained to automatically map documents to these abstract concepts, allowing to annotate ve...

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

IEEE transactions on pattern analysis and machine intelligence
Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute corr...

Automated Training of Deep Convolutional Neural Networks for Cell Segmentation.

Scientific reports
Deep Convolutional Neural Networks (DCNN) have recently emerged as superior for many image segmentation tasks. The DCNN performance is however heavily dependent on the availability of large amounts of problem-specific training samples. Here we show t...