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Found 11 papers, 3 papers with code
Semantic Lens: Instance-Centric Semantic Alignment for Video Super-Resolution
As a critical clue of video super-resolution (VSR), inter-frame alignment significantly impacts overall performance.
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks
This neural network architecture, which we call symplectic gyroceptron, ensures that the resulting surrogate map is nearly-periodic and symplectic, and that it gives rise to a discrete-time adiabatic invariant and a long-time stability.
Image Translation Based Nuclei Segmentation for Immunohistochemistry Images
Numerous deep learning based methods have been developed for nuclei segmentation for H&E images and have achieved close to human performance.
Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems
We present a data-driven modeling method that accurately captures shocks and chaotic dynamics by proposing a novel architecture, stabilized neural ordinary differential equation (ODE).
Network analysis regarding international trade network
We study the effect of globalization of world economy between 1980 and 2010 by using network analysis technics on trade and GDP data of 71 countries in the world.
Artificial Neural Network and its Application Research Progress in Distillation
Artificial neural networks learn various rules and algorithms to form different ways of processing information, and have been widely used in various chemical processes.
BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation
The other is the content guidance bridge (CGBdg) designed for the depth map reconstruction process, which provides the content guidance learned from DSR task for MDE task.
Prediction of financial time series using LSTM and data denoising methods
As WT and SSA can extract useful information from the original sequence and avoid overfitting, the hybrid model can better grasp the sequence pattern of the closing price of the DJIA.
SuperCell: A Wide-Area Coverage Solution Using High-Gain, High-Order Sectorized Antennas on Tall Towers
Finally, in this article we also shed light on two recent SuperCell field trials performed using a Luneburg lens antenna system.
Deep Learning Derived Histopathology Image Score for Increasing Phase 3 Clinical Trial Probability of Success
Failures in Phase 3 clinical trials contribute to expensive cost of drug development in oncology.
EasyQuant: Post-training Quantization via Scale Optimization
The 8 bits quantization has been widely applied to accelerate network inference in various deep learning applications.
