DsODENet: Neural ODE and Depthwise Separable Convolution for Domain Adaptation on FPGAs

Business & Economics

• Convolution 100%
• Differential Equations 93%
• Neural Networks 42%
• Resources 22%
• Computational Complexity 21%
• Resource Utilization 20%
• Network Model 17%
• High Performance 16%
• Inference 14%
• Software 11%

Engineering & Materials Science

• Ordinary differential equations 75%
• Convolution 69%
• Field programmable gate arrays (FPGA) 57%
• Deep neural networks 34%
• Data storage equipment 21%
• Image classification 18%
• Computational complexity 14%