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Tech Xplore1d
New framework reduces memory usage and boosts energy efficiency for large-scale AI graph analysis
BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...
IEEE3mon
Binary Convolution Model for Image Classification - IEEE Xplore
The latter network is meant to be the standard Fully Connected Layer that is included as the final stage of a typical Convolutional Neural Network (CNN), after which a Soft Max function does the final ...
Scientific Research Publishing9mon
Performance Comparison of Vision Transformer- and CNN-Based Image Classification Using Cross Entropy: A Preliminary Application to Lung Cancer Discrimination from CT Images
This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images ...
GitHub1y
GitHub - debdattasarkar/Image-Classification-with-CNN-in-TensorFlow: Image Classification with Convolutional Neural Networks in TensorFlow: Fashion Item Classifier
Using the Fashion MNIST dataset, you decide to construct a Convolutional Neural Network (CNN) that can swiftly and accurately classify images into one of ten fashion categories. To enhance your ...
Visual Studio Magazine3y
Convolutional Neural Networks for MNIST Data Using PyTorch
In principle it's possible to create a neural network classifier for MNIST data using just a single linear layer that accepts 784 input values and emits 10 logits or pseudo-probabilities. But this ...