AIMC Topic: Pattern Recognition, Automated
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Semisupervised Deep Stacking Network with Adaptive Learning Rate Strategy for Motor Imagery EEG Recognition.
Neural computation
Mar 18, 2019
Practical motor imagery electroencephalogram (EEG) data-based applications are limited by the waste of unlabeled samples in supervised learning and excessive time consumption in the pretraining period. A semisupervised deep stacking network with an a...
Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia.
Neural computation
Mar 18, 2019
Machine learning (ML) is a growing field that provides tools for automatic pattern recognition. The neuroimaging community currently tries to take advantage of ML in order to develop an auxiliary diagnostic tool for schizophrenia diagnostics. In this...
A dense multi-path decoder for tissue segmentation in histopathology images.
Computer methods and programs in biomedicine
Mar 14, 2019
BACKGROUND AND OBJECTIVE: Segmenting different tissue components in histopathological images is of great importance for analyzing tissues and tumor environments. In recent years, an encoder-decoder family of convolutional neural networks has increasi...
Analysis and evaluation of handwriting in patients with Parkinson's disease using kinematic, geometrical, and non-linear features.
Computer methods and programs in biomedicine
Mar 13, 2019
BACKGROUND AND OBJECTIVES: Parkinson's disease is a neurological disorder that affects the motor system producing lack of coordination, resting tremor, and rigidity. Impairments in handwriting are among the main symptoms of the disease. Handwriting a...
Convolutional neural network for cell classification using microscope images of intracellular actin networks.
PloS one
Mar 13, 2019
Automated cell classification is an important yet a challenging computer vision task with significant benefits to biomedicine. In recent years, there have been several studies attempted to build an artificial intelligence-based cell classifier using ...
Cytoplasm
Cytoskeleton
Automation
Pattern Recognition, Automated
Actins
Models, Statistical
Humans
Cell Line, Tumor
Algorithms
MCF-7 Cells
Neural Networks, Computer
Image Processing, Computer-Assisted
Female
Microscopy, Fluorescence
Machine Learning
Cell Line
Reproducibility of Results
Breast
Breast Neoplasms
Feature Aggregation With Reinforcement Learning for Video-Based Person Re-Identification.
IEEE transactions on neural networks and learning systems
Mar 12, 2019
Video-based person re-identification (re-id) matches two tracks of persons from different cameras. Features are extracted from the images of a sequence and then aggregated as a track feature. Compared to existing works that aggregate frame features b...
Discriminative multi-source adaptation multi-feature co-regression for visual classification.
Neural networks : the official journal of the International Neural Network Society
Mar 12, 2019
Learning an effective visual classifier from few labeled samples is a challenging problem, which has motivated the multi-source adaptation scheme in machine learning. While the advantages of multi-source adaptation have been widely recognized, there ...
Offline and online myoelectric pattern recognition analysis and real-time control of a robotic hand after spinal cord injury.
Journal of neural engineering
Mar 5, 2019
OBJECTIVE: The objective of this study was to investigate the feasibility of applying myoelectric pattern recognition for controlling a robotic hand in individuals with spinal cord injury (SCI).
Automated detection of koalas using low-level aerial surveillance and machine learning.
Scientific reports
Mar 1, 2019
Effective wildlife management relies on the accurate and precise detection of individual animals. These can be challenging data to collect for many cryptic species, particularly those that live in complex structural environments. This study introduce...
Deep Attention Network for Egocentric Action Recognition.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 26, 2019
Recognizing a camera wearer's actions from videos captured by an egocentric camera is a challenging task. In this paper, we employ a two-stream deep neural network composed of an appearance-based stream and a motion-based stream to recognize egocentr...
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