| 複數 | ltms |
stored in ltm
Traditional Chinese_translation
in ltm
Traditional Chinese_translation
update ltm
Traditional Chinese_translation
ltm storage
Traditional Chinese_translation
the ltm network processes information over extended periods of time.
長期記憶網絡會在較長的時間內處理資訊。
neural networks develop ltm through repeated learning cycles.
神經網絡透過反覆的學習週期來發展長期記憶。
the hippocampus plays a crucial role in ltm consolidation.
海馬體在長期記憶的鞏固過程中扮演著關鍵角色。
ltm storage capacity significantly exceeds that of short-term memory.
長期記憶的儲存容量顯著超過短期記憶。
researchers study ltm retrieval patterns in deep learning models.
研究人員研究深度學習模型中的長期記憶提取模式。
the ltm mechanism enables persistent knowledge retention in ai systems.
長期記憶機制使人工智能系統能夠持續保留知識。
understanding ltm formation helps improve neural network architecture.
了解長期記憶的形成有助於改進神經網絡結構。
artificial intelligence relies on ltm for complex problem solving.
人工智慧依賴長期記憶來進行複雜的問題解決。
the ltm system simulates human memory consolidation processes.
長期記憶系統模擬人類記憶鞏固的過程。
computational neuroscience models simulate ltm retrieval mechanisms.
計算神經科學模型模擬長期記憶的提取機制。
ltm development requires sustained and repeated neural activation patterns.
長期記憶的發展需要持續且反覆的神經活化模式。
the brain's ltm capacity allows for vast information storage over lifetimes.
大腦的長期記憶容量允許在一生中儲存龐大的資訊。
stored in ltm
Traditional Chinese_translation
in ltm
Traditional Chinese_translation
update ltm
Traditional Chinese_translation
ltm storage
Traditional Chinese_translation
the ltm network processes information over extended periods of time.
長期記憶網絡會在較長的時間內處理資訊。
neural networks develop ltm through repeated learning cycles.
神經網絡透過反覆的學習週期來發展長期記憶。
the hippocampus plays a crucial role in ltm consolidation.
海馬體在長期記憶的鞏固過程中扮演著關鍵角色。
ltm storage capacity significantly exceeds that of short-term memory.
長期記憶的儲存容量顯著超過短期記憶。
researchers study ltm retrieval patterns in deep learning models.
研究人員研究深度學習模型中的長期記憶提取模式。
the ltm mechanism enables persistent knowledge retention in ai systems.
長期記憶機制使人工智能系統能夠持續保留知識。
understanding ltm formation helps improve neural network architecture.
了解長期記憶的形成有助於改進神經網絡結構。
artificial intelligence relies on ltm for complex problem solving.
人工智慧依賴長期記憶來進行複雜的問題解決。
the ltm system simulates human memory consolidation processes.
長期記憶系統模擬人類記憶鞏固的過程。
computational neuroscience models simulate ltm retrieval mechanisms.
計算神經科學模型模擬長期記憶的提取機制。
ltm development requires sustained and repeated neural activation patterns.
長期記憶的發展需要持續且反覆的神經活化模式。
the brain's ltm capacity allows for vast information storage over lifetimes.
大腦的長期記憶容量允許在一生中儲存龐大的資訊。
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