[paper]End-to-End Training of Hybrid CNN-CRF Models for Stereo
Pre-learning 隱馬爾科夫模型 Y={y1,y2,...,yn} 是一組隨機變量， X={x1,x2,...,xn} 是其觀測變量，我們假設Y具有馬爾科夫性，則X，Y的聯合概率爲 P(x1,x2,...,xn,y1,y2,...,yn)=P(y1)P(x1|y1)∏i=2nP(yi|yi−1)P(xi|yi) 爲確定一個Hidden Markov Model，需要確定以下三組參數 [A,
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相關文章
- 1. 論文筆記《End-to-End Training of Hybrid CNN-CRF Models for Stereo》用於立體評估的端到端訓練的混合CNN-CRF模型
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- 8. BERT:Pre-training of Deep Bidirectional Transformers for Language Understanding
- 9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- 10. 《BERT:Pre-training of Deep Bidirectional Transformers for Language Understanding》