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Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
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Zhaoming Li, Xinyan Yang, Lei Li and Hang Chen
In order to increase a nonlinear system?s state estimate precision, an iterated orthogonal simplex cubature Kalman filter (IOSCKF) is presented in this study for target tracking. The Gaussian-weighted integral is decomposed into a spherical integral and ...
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Olga Kurasova, Arnoldas Bud?ys and Viktor Medvedev
As artificial intelligence has evolved, deep learning models have become important in extracting and interpreting complex patterns from raw multidimensional data. These models produce multidimensional embeddings that, while containing a lot of informatio...
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Evgeniya Ermakova, Sergey Sysoev, Irina Tsyrendorzhieva, Alexander Mareev, Olga Maslova, Vladimir Shayapov, Eugene Maksimovskiy, Irina Yushina and Marina Kosinova
We report an investigation into 1,4-Bis-N,N-(trimethylsilyl)piperazine (BTMSP) as a novel precursor for the synthesis of silicon carbonitride films by chemical vapor deposition (CVD). The thermal stability, temperature dependence of vapor pressure and th...
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Zixin Feng, Teligeng Yun, Yu Zhou, Ruirui Zheng and Jianjun He
Geometric mean metric learning (GMML) algorithm is a novel metric learning approach proposed recently. It has many advantages such as unconstrained convex objective function, closed form solution, faster computational speed, and interpretability over oth...
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