期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Revolutionizing neuromorphic computing:brain-like functions emerge from standard silicon transistors
1
作者 Yuchen Cai Ruiqing Cheng +1 位作者 Yao Cai Jun He 《Science Bulletin》 2025年第20期3299-3301,共3页
Artificial neural networks(ANNs)promise revolutionary advances in artificial intelligence(AI)but face critical hardware limitations.While offering unprecedented computational power for tasks like object recognition an... Artificial neural networks(ANNs)promise revolutionary advances in artificial intelligence(AI)but face critical hardware limitations.While offering unprecedented computational power for tasks like object recognition and natural language processing,their hardware implementations encounter physical constraints[1]. 展开更多
关键词 object recognition hardware limitations artificial neural networks hardware implementations artificial neural networks anns promise natural language processingtheir standard silicon transistors artificial intelligence
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部