According to DeepLearning.AI, Meta has launched a comprehensive open-weights image segmentation suite featuring SAM 3 for segmenting images and videos—including from text prompts—SAM 3D Objects for ...
Abstract: In this paper, we propose a novel approach to minimize the inference delay in semantic segmentation using split learning (SL), tailored to the needs of real-time computer vision (CV) ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Correlative imaging is a powerful analytical approach in bioimaging, as it offers ...
Spiking Neural Networks (SNNs), inspired by neuroscience principles, have gained attention for their energy efficiency. However, directly trained SNNs lag behind Artificial Neural Networks (ANNs) in ...
School of Mechanical Engineering, Purdue University, West Lafayette, IN, United States Automated docking technologies for marine vessels have advanced significantly, yet trailer loading, a critical ...
ABSTRACT: Contour is an important pattern descriptor in image processing and particularly in region description, registration and length estimation. In many applications where contour is used, a good ...
What if you could teach a computer to recognize a zebra without ever showing it one? Imagine a world where object detection isn’t bound by the limits of endless training data or high-powered hardware.
Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...
In a world characterized by rapidly shifting technology, it’s difficult to know which advancements are here for the long haul and which are fleeting. It’s even more difficult for companies to ...
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