JavaShuo
欄目
標籤
Boosting Adversarial Training with Hypersphere Embedding
時間 2021-05-08
標籤
neural networks
欄目
C&C++
简体版
原文
原文鏈接
文章目錄 概 主要內容 代碼 Pang T., Yang X., Dong Y., Xu K., Su H., Zhu J. Boosting Adversarial Training with Hypersphere Embedding. arXiv preprint arXIv 2002.08619 概 在最後一層, 對weight和features都進行normalize有助於加強對抗訓練.
>>阅读原文<<
相關文章
1.
[paper]Boosting Adversarial Attacks with Momentum
2.
SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification (note)
3.
論文解讀《Boosting Adversarial Attacks with Momentum》
4.
NORMFACE:L2 hypersphere embedding for face Verification
5.
SphereFace Deep Hypersphere Embedding for Face Recognition
6.
SphereFace: Deep Hypersphere Embedding for Face Recognition
7.
NormFace L2 Hypersphere Embedding for Face Verification
8.
NormFace: L2 Hypersphere Embedding for Face Verification
9.
Black Box Adversarial Attack With Transferable Model Based Embedding
10.
關於《Domain Adaptation with Adversarial Training and Graph Embeddings》的理解
更多相關文章...
•
XSLT
元素
-
XSLT 教程
•
Docker 容器連接
-
Docker教程
•
爲了進字節跳動,我精選了29道Java經典算法題,帶詳細講解
•
算法總結-股票買賣
相關標籤/搜索
adversarial
boosting
embedding
training
embedding+lstm
flink training
with+this
with...connect
with...as
by...with
C&C++
0
分享到微博
分享到微信
分享到QQ
每日一句
每一个你不满意的现在,都有一个你没有努力的曾经。
最新文章
1.
NLP《詞彙表示方法(六)ELMO》
2.
必看!RDS 數據庫入門一本通(附網盤鏈接)
3.
阿里雲1C2G虛擬機【99/年】羊毛黨集合啦!
4.
10秒鐘的Cat 6A網線認證儀_DSX2-5000 CH
5.
074《從零開始學Python網絡爬蟲》小記
6.
實例12--會動的地圖
7.
聽薦 | 「談笑風聲」,一次投資圈的嘗試
8.
阿里技術官手寫800多頁PDF總結《精通Java Web整合開發》
9.
設計模式之☞狀態模式實戰
本站公眾號
歡迎關注本站公眾號,獲取更多信息
相關文章
1.
[paper]Boosting Adversarial Attacks with Momentum
2.
SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification (note)
3.
論文解讀《Boosting Adversarial Attacks with Momentum》
4.
NORMFACE:L2 hypersphere embedding for face Verification
5.
SphereFace Deep Hypersphere Embedding for Face Recognition
6.
SphereFace: Deep Hypersphere Embedding for Face Recognition
7.
NormFace L2 Hypersphere Embedding for Face Verification
8.
NormFace: L2 Hypersphere Embedding for Face Verification
9.
Black Box Adversarial Attack With Transferable Model Based Embedding
10.
關於《Domain Adaptation with Adversarial Training and Graph Embeddings》的理解
>>更多相關文章<<