We introduce robust evaluation metrics, including the proportion of area under the curve (AUC) of probability density functions (PDFs) ≥ 70 % accuracy, overlap coefficients, and percentile-based ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

The softmax function used in Transformer’s attention mechanism tends to distribute attention scores across all tokens, even those that are not relevant to the task.

High-dimension features of electrical substation equipment images were first extracted by classical pre-trained DCNN architectures through the transfer learning method, and different incipient faults ...

Hello, I have some trouble to compile composable_kernel for my AMD GPU architecture (gfx1010) ...

Two types of representative DNNs, the ResNet (He et al., 2016) and DenseNet (Huang et al., 2017), were chosen as the backbone network of the feature recognition module. The recognition of ER whorls, ...

Deep Learning Framework only using numpy: Linear, Convolution, Flatten, Max and Mean Pooling layers, activation functions, Softmax, MSE and Cross Entropy. Useful functions: train, save an load a model ...