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Pengfei Zhao and Ze Liu
The three-dimensional (3D) reconstruction of Electromagnetic Tomography (EMT) is an important task for many applications, such as the non-destructive testing of inner defects in rail systems. Additionally, image reconstruction algorithms utilizing deep l...
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Chuanyun Xu, Hang Wang, Yang Zhang, Zheng Zhou and Gang Li
Few-shot learning refers to training a model with a few labeled data to effectively recognize unseen categories. Recently, numerous approaches have been suggested to improve the extraction of abundant feature information at hierarchical layers or multipl...
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Damian Valdés-Santiago, Angela M. León-Mecías, Marta Lourdes Baguer Díaz-Romañach, Antoni Jaume-i-Capó, Manuel González-Hidalgo and Jose Maria Buades Rubio
This contribution presents a wavelet-based algorithm to detect patterns in images. A two-dimensional extension of the DST-II is introduced to construct adapted wavelets using the equation of the tensor product corresponding to the diagonal coefficients i...
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Yun-Wei Lin, Yuh-Hwan Liu, Yi-Bing Lin and Jian-Chang Hong
Deep learning models are often trained with a large amount of labeled data to improve the accuracy for moving object detection in new fields. However, the model may not be robust enough due to insufficient training data in the new field, resulting in som...
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Kristoffer Vinther Olesen, Ahcène Boubekki, Michael C. Kampffmeyer, Robert Jenssen, Anders Nymark Christensen, Sune Hørlück and Line H. Clemmensen
The analysis of maritime traffic patterns for safety and security purposes is increasing in importance and, hence, Vessel Traffic Service operators need efficient and contextualized tools for the detection of abnormal maritime behavior. Current models la...
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