Ship Type Recognition via a Coarse-to-Fine Cascaded Convolution Neural Network
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Navigation"
DOI: 10.1017/s0373463319000900
Abstract: Most previous research has handled the task of ship type recognition by exploring hand-craft ship features, which may fail to distinguish ships with similar visual appearances. This situation motivates us to propose a novel deep… read more here.
Keywords: ship; ship type; type recognition; coarse fine ... See more keywords
Change Type Recognition for SAR Images Using Statistical Bidirectional LSTM Network With Few Labeled Samples
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3222794
Abstract: Change detection in synthetic aperture radar (SAR) images has garnered significant research interest. However, to date, only the change area can be obtained, which seriously restricts further development of SAR image applications. To solve this… read more here.
Keywords: type recognition; change; lstm network; sar images ... See more keywords
A Sequence-to-Sequence Deep Learning Architecture Based on Bidirectional GRU for Type Recognition and Time Location of Combined Power Quality Disturbance
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2019.2895054
Abstract: In this paper, a sequence-to-sequence deep learning architecture based on the bidirectional gated recurrent unit (Bi-GRU) for type recognition and time location of combined power quality disturbance is proposed. Especially, the proposed methodology can determine… read more here.
Keywords: type recognition; sequence; sequence sequence; input sequence ... See more keywords
Vehicle Type Recognition From Surveillance Data Based on Deep Active Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2020.2967077
Abstract: Vehicle type recognition (VTR) from surveillance data has recently received increasing attention in both intelligent transportation and computer vision field. The deep learning techniques, e.g., convolutional neural networks (CNNs), have provided great progress in tasks… read more here.
Keywords: surveillance; type recognition; based deep; framework ... See more keywords
Geological Type Recognition by Machine Learning on In-Situ Data of EPB Tunnel Boring Machines
Sign Up to like & getrecommendations! Published in 2020 at "Mathematical Problems in Engineering"
DOI: 10.1155/2020/3057893
Abstract: At present, many large-scale engineering equipment can obtain massive in-situ data at runtime. In-depth data mining is conducive to the real-time understanding of equipment operation status or recognition of service environment. This paper proposes a… read more here.
Keywords: machine; tunnel; recognition; situ data ... See more keywords