To address the class imbalance (in the number of images/masks) between the Hemorrhagic and Ischemic classes of the original CT image dataset, we applied our offline augmentation tools, ...
Abstract: With an emphasis on convolutional neural networks (CNNs), this research does a thorough analysis of the effectiveness and suitability of the TensorFlow and PyTorch frameworks for image ...
This is the first experiment of Image Segmentation for EBHI-Colorectal-Cancer based on our TensorFlowFlexUNet (TensorFlow Flexible UNet Image Segmentation Model for Multiclass) and, 512x512 pixels ...
Abstract: As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural ...
The well-funded and innovative French AI startup Mistral AI is introducing a new service for enterprise customers and independent software developers alike. Mistral's Agents application programming ...
A new AI model, H-CAST, groups fine details into object-level concepts as attention moves from lower to high layers, outputting a classification tree—such as bird, eagle, bald eagle—rather than ...
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