October 2014
Intermediate to advanced
288 pages
6h 27m
Japanese
Content preview from 実践 機械学習システム
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202
10
章 コンピュータビジョン：パターン認識
まで機械学習を行うために学んできたNumPyの操作を、全く別の問題でも利用することができます。
最後に二つの画像を合成します。中心部分を鮮明に、周辺部分へ行くに従ってソフトになるように
します（図10-9）。
ringed = mh.stretch(im*W + (1-W)*im12)
図10-9
以上で、フィルタ処理の基本的な手法の説明を終わります。これで、新しいフィルタを作ることもで
きるでしょう。これまで見てきて感じたかもしれませんが、この分野は科学というよりも芸術に近い分
野だと言えます。
10.2.3
パターン認識
画像を識別するとき、対象とするのは数値（ピクセル値）からなる大きな長方形の配列です。最近で
はピクセルの数が何百万であるというのは一般的です。
全てのピクセルを特徴量として学習アルゴリズムに与えることは可能です。しかし、それは良い考
えではありません。なぜなら、各ピクセルの関連性（もしくは小さいピクセル領域の関連性）は最終的
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