TABLE 2. Structure of complex-valued convolutional neural network (CVCNN). Layer typeLayer parameterActivation function Input 1x2x4096 CvConv1 1, 64, kernel size (2x3), stride 1, padding 0 ReLU BN+MaxP kernel
Moreover, the integration of complex-number operations—including complex convolution, normalization, and activation functions—within CVNNs inherently constrains the solution space, thereby effectively addressing light wave diffraction. Section snippets Algorithm framework of CVNN Using the iterative projection ...
All experiments were implemented in PyTorch and run on workstations equipped with Intel Xeon(R) CPUs, GeForce RTX 2080Ti GPUs and 64 GB of RAM. In the comparison experiments, RCSFFCNet uses the same encoder configurations as Resnet18, with real-valued models (RF, VGG16, Resnet18, UNet)...
🧠The intricacies of FastAI and PyTorch.Prior to this project, I worked primarily in TensorFlow - thanks to this project, I learned how to implement custom activation functions and layer models in PyTorch and use a mixture of mid-level FastAI APIs (such as DataBlocks and DataLoaders) to cr...
We implemented our network using the publicly available and well-known PyTorch package on Tesla p100 GPUs. In the CDNNet model, the feature extraction network for each branch and the teacher network for knowledge distillation adopt the ResNet-50 pre-trained on ImageNet. Following [6], we extra...
introduced CV-CNNs for the classification of synthetic aperture radar (SAR) images, investigating the impact of various complex-valued activation functions on classifier performance [27]. They also creatively proposed the complex-valued adaptive moment estimation (CV-Adam) optimization algorithm tailored ...
In CvNN, the data, weight and activation function are all located in the complex field, and their operations are in the complex domain. It is known that one complex-valued FLOP is equivalent to four real-valued FLOPs. Therefore, FLOPs in the CvNN should be multiplied by four times on the...
In CvNN, the data, weight and activation function are all located in the complex field, and their operations are in the complex domain. It is known that one complex-valued FLOP is equivalent to four real-valued FLOPs. Therefore, FLOPs in the CvNN should be multiplied by four times on the...