We propose a local fractal dimension based nearest neighbor classifier for ECG based
classification of arrhythmia. Local fractal dimension (LFD) at each sample point of the ECG …

以机器学习为主的雷达目标识别模型性能由模型与数据共同决定. 当前雷达目标识别评估依赖于
准确性评估指标, 缺乏数据质量对识别性能影响的评估指标. 数据可分性描述了属于不同类别 …

In machine learning, the performance of a classifier depends on both the classifier model
and the separability/complexity of datasets. To quantitatively measure the separability of …

Signal detection theory (SDT), the standard mathematical framework by which we
understand how stimuli are classified into distributions such as signal or noise, is an …

In machine learning, the performance of a classifier depends on both the classifier model
and the dataset. For a specific neural network classifier, the training process varies with the …

Multispectral satellite imageries (MSIs) are strong enough to delineate features of interest by
suppressing others. The water index is a method applied to delineate the water features by …

Abstract Machine learning and deep learning classification models are data-driven, and the
model and the data jointly determine their classification performance. It is biased to evaluate …

Target detection and classification are two major uses of a Radar system. The usual way a
Radar (or any sensor-system) operates is by sensing data from the environment and then …

Abstract The applications of Deep Learning (DL) for medical imaging have become
increasingly popular in recent years. During my studies of applications of Machine Learning …

Pulse coupled neural network (PCNN) framework is proposed in this paper for scale,
position, elevation and illumination invariant synthetic aperture radar (SAR) automatic target …