Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...
Abstract: Large-scale, big-variant, high-quality data are crucial for developing robust and successful deep-learning models for medical applications since they potentially enable better generalization ...
Overview of VeloxSeg. VeloxSeg employs an encoder-decoder architecture with Paired Window Attention (PWA) and Johnson-Lindenstrauss lemma-guided convolution (JLC) on the left, using 1x1 convolution as ...
This study implements a deep learning workflow for calcification detection and segmentation using Python. The pipeline consists of multiple components, including a Variational Autoencoder (VAE), ...
An action-packed Sunday across the NFL wraps up in East Rutherford, N.J., when the New York Giants play host to the Kansas City Chiefs. Both teams are 0-2, and if you’re trying to bet on one of them ...
Despite the rapid adoption of LLM chatbots, little is known about how they are used. We document the growth of ChatGPT’s consumer product from its launch in November 2022 through July 2025, when it ...
The first step is to generate an image. You can use any tool to generate an image. I have used Meta AI and Google AI Studio. I generated two images using the simple prompts written below: A dog riding ...
Abstract: Accurate 3D medical image segmentation is crucial for diagnosis and treatment. Diffusion models demonstrate promising performance in medical image segmentation tasks due to the progressive ...
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