Abstract: Improving the quality of underwater images is essential for advancing marine research and technology. This work introduces a sparsity-driven interpretable neural network (SINET) for the ...
Combining newer neural networks with older AI systems could be the secret to building an AI to match or surpass human ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...
Blending ‘old-fashioned’ logic systems with the neural networks that power large language models is one of the hottest trends ...
Sber opens weights of two new flagship MoE models in the GigaChat series — Ultra Preview and Lightning — trained from scratch ...
Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...
This guide shows how TPUs crush performance bottlenecks, reduce training time, and offer immense scalability via Google Cloud ...
This valuable study uses mathematical modeling and analysis to address the question of how neural circuits generate distinct low-dimensional, sequential neural dynamics that can change on fast, ...
Abstract: We proposed and demonstrated experimentally a random code radar with range-time–frequency points and the improved PointConv network for through-wall human action recognition (HAR). The ...
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