Abstract: Deep learning-based approaches to hyperspectral image analysis have attracted large attention and exhibited high performance in image classification tasks. However, deployment of deep ...
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 ...
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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