Content-Length: 223638 | pFad | http://b.hatena.ne.jp/AKIMOTO/%E7%B4%B9%E4%BB%8B%E3%81%97%E3%81%9F/%E7%99%96/
GradType BatlleGround
We have trained a neural network to identify the users by their manner of typing on keyboard. The recurrent neural network learned to recognize small timing difference between keypresses to successfully identify the "typer" given 30-40 previously seen sentences. Type few sentences below to play with it or log in with GitHub to store your identifiers for extensive testing (and further improvement o
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リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Fetched URL: http://b.hatena.ne.jp/AKIMOTO/%E7%B4%B9%E4%BB%8B%E3%81%97%E3%81%9F/%E7%99%96/
Alternative Proxies:
GitHub - indutny/gradtype: WIP
