Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.
The company is positioning it as especially good for enterprise use. The company is positioning it as especially good for enterprise use. is The Verge’s senior AI reporter. An AI beat reporter for ...
Python has become one of the most popular programming languages out there, particularly for beginners and those new to the hacker/maker world. Unfortunately, while it’s easy to get something up and ...
AI Microsoft CEO warns that we must 'do something useful' with AI or they'll lose 'social permission' to burn electricity on it AI Steam updates AI disclosure form to specify that it's focused on ...
An ordinance and a resolution approved by Portland City Council on Wednesday aim to strengthen the city’s sanctuary status and use all available legal resources to resist deployment of any federal ...
I've run Python 3.10.18 with SQL Alchemy 1.4.39 to create a connection to MS SQL Server DB on macOS 15.6.1 and I get the error: Extension modules: charset_normalizer.md, google._upb._message, ...
For startups and established businesses, understanding the importance of segmentation is essential for the granular analysis of consumer demographics, behaviors, needs, and preferences. These insights ...
Google Colab, also known as Colaboratory, is a free online tool from Google that lets you write and run Python code directly in your browser. It works like Jupyter Notebook but without the hassle of ...
Users have been testing Google's new image editing model "Nano Banana" — aka Gemini 2.5 Flash Image – for a few days, with some testers posting samples of images generated with the new AI model or ...
The Python team at Microsoft is continuing its overhaul of environment management in Visual Studio Code, with the August 2025 release advancing the controlled rollout of the new Python Environments ...
Siqi Zhang*, Qizhe Zhang*, Shanghang Zhang*†, Xiaohong Liu*, Jingkun Yue*, Ming Lu, Huihuan Xu, Jiaxin Yao, Xiaobao Wei, Jiajun Cao, Xiang Zhang, Ming Gao, Jun Shen ...
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