[過去ﾛｸﾞ] 【統計分析】機械学習・データマイニング20 (1002ﾚｽ)
上下前次1-新
抽出解除 必死ﾁｪｯｶｰ(本家) (べ) 自ID ﾚｽ栞 あぼーん

---

このｽﾚｯﾄﾞは過去ﾛｸﾞ倉庫に格納されています｡
次ｽﾚ検索 歴削→次ｽﾚ 栞削→次ｽﾚ 過去ﾛｸﾞﾒﾆｭｰ

---

ﾘﾛｰﾄﾞ規制です｡10分ほどで解除するので､他のﾌﾞﾗｳｻﾞへ避難してください｡

---

718(1): (ﾜｯﾁｮｲ d980-A6IM) 2018/10/07(日)21:24 ID:mIq+f5AO0(1) AAS
外部ﾘﾝｸ[pdf]:arxiv.org
> 3.2 Global Average Pooling

> ・・・
> However, the fully connected layers are prone to overfitting, thus hampering the generalization ability
> of the overall network. Dropout is proposed by Hinton et al. [5] as a regularizer which randomly
> sets half of the activations to the fully connected layers to zero during training. It has improved the
> generalization ability and largely prevents overfitting [4].

> In this paper, we propose another strategy called global average pooling to replace the traditional
> fully connected layers in CNN.

---

上下前次1-新書関写板覧索設栞歴

---

ｽﾚ情報 赤ﾚｽ抽出 画像ﾚｽ抽出 歴の未読ｽﾚ

---

ぬこの手 ぬこTOP 0.037s