AIMC Topic: Pattern Recognition, Automated

Clear Filters Showing 601 to 610 of 1689 articles

All-optical spiking neurosynaptic networks with self-learning capabilities.

Nature
Software implementations of brain-inspired computing underlie many important computational tasks, from image processing to speech recognition, artificial intelligence and deep learning applications. Yet, unlike real neural tissue, traditional computi...

BoSR: A CNN-based aurora image retrieval method.

Neural networks : the official journal of the International Neural Network Society
The deep learning models especially the CNN have achieved amazing performance on natural image retrieval. However, remote sensing images captured with anamorphic lens are still retrieved via manual selection or traditional SIFT-based methods. How to ...

Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: We address the automatic segmentation of healthy and cancerous liver tissues (parenchyma, active and necrotic parts of hepatocellular carcinoma (HCC) tumor) on multiphase CT images using a deep learning approach.

Segmenting and classifying activities in robot-assisted surgery with recurrent neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Automatically segmenting and classifying surgical activities is an important prerequisite to providing automated, targeted assessment and feedback during surgical training. Prior work has focused almost exclusively on recognizing gestures, o...

Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition.

IEEE transactions on cybernetics
Brain-computer interface (BCI) is a system empowering humans to communicate with or control the outside world with exclusively brain intentions. Electroencephalography (EEG)-based BCI is one of the promising solutions due to its convenient and portab...

Using Surgeon Hand Motions to Predict Surgical Maneuvers.

Human factors
OBJECTIVE: This study explores how common machine learning techniques can predict surgical maneuvers from a continuous video record of surgical benchtop simulations.

Photomontage detection using steganography technique based on a neural network.

Neural networks : the official journal of the International Neural Network Society
This article presents a steganographic method StegoNN based on neural networks. The method is able to identify a photomontage from presented signed images. Unlike other academic approaches using neural networks primarily as classifiers, the StegoNN m...

Hypercomplex extreme learning machine with its application in multispectral palmprint recognition.

PloS one
An extreme learning machine (ELM) is a novel training method for single-hidden layer feedforward neural networks (SLFNs) in which the hidden nodes are randomly assigned and fixed without iterative tuning. ELMs have earned widespread global interest d...

Dense networks with relative location awareness for thorax disease identification.

Medical physics
PURPOSE: Chest X-ray is one of the most common examinations for diagnosing heart and lung diseases. Due to the existing of a large number of clinical cases, many automated diagnosis algorithms based on chest X-ray images have been proposed. To our kn...