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9 RegisterLog in Sign up with one click: Facebook Twitter Google Share on Facebook target classification A grouping of targets in accordance with their threat to the amphibious task force and its component elements: targets not to be fired upon prior to D-day and targets not to be destroyed...
Ang, G. Lim, Target classification using knowledge-based probabilistic model, in: Proceedings of the 14th International Conference on fusion (FUSION), 2011.W. Tang, K. Z. Mao, L. O. Mak, G. W. Ng, Z. Sun, J. H. Ang, and G. Lim. Target classification using knowledge-based ...
The multifractal characteristics of return signals from aircraft targets in conventional radars offer a fine description of dynamic characteristics which induce the targets' echo structure; therefore they can provide a new way for aircraft target classification and recognition with low-resolution surveillance...
Target classification is an important function in modern radar systems. This example uses machine and deep learning to classify radar echoes from a cylinder and a cone. Although this example uses the synthesized I/Q samples, the workflow is applicable to real radar returns. RCS Synthesis ...
Deep feature extraction and combination for synthetic aperture radar target classification Inspired by the great success of convolutional neural network (CNN), we address the problem of SAR target classification by proposing a feature extraction ... M Amrani,F Jiang - 《Journal of Applied Remote Sen...
CLASSIFICATION SYSTEM [Problem] To make it possible to explain the basis for a classification and to verify the suitability of said classification by constructing a database of ... H Shinkichi 被引量: 0发表: 2020年 Double groups of gates based Takagi-Sugeno-Kang (DG-TSK) fuzzy system for ...
Specifically, this problem is addressed in the context of underwater mine classification where the objective is to discriminate targets (i.e., mines) from benign clutter (e.g., rocks) when each object is observed in an arbitrary number of synthetic aperture sonar (SAS) images. The proposed ...
Deep convolutional neural networks are used to perform underwater target classification in synthetic aperture sonar (SAS) imagery. The deep networks are learned using a massive database of real, measured sonar data collected at sea during different expeditions in various geographical locations. A novel...
这篇文章的主要思想是通过构造一个“标签混淆模型”来实时地“想象”一个比one-hot更好的标签分布,从而使得各种深度学习模型(LSTM、CNN、BERT)在分类问题上都能得到更好的效果。个人感觉,还是有、意思的。论文标题:Label Confusion Learning to Enhance Text Classification Models 会议/期刊:AAAI-21 团队:上海财经...