Papers with Code 아카이브

Classification Consistency

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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How often two shifts of the same image are classified the same

<span style="color:grey; opacity: 0.6">( Image credit: Antialiased CNNs )</span>

기법

관련 논문에서 소개한 기법입니다. 이 태스크에서의 평가 여부는 평가 결과에서 확인하세요.

Anti-Alias Downsampling

Anti-Alias Downsampling (AA) aims to improve the shift-equivariance of deep networks. Max-pooling is inherently composed of two operations. The first operation is to densely evaluate the max operator and second operation is naive subsampling. AA is proposed as a low-pass filter between them to achieve practical anti-aliasing in any existing strided layer such as strided convolution. The smoothing factor can be adjusted by changing the blur kernel filter size, where a larger filter size results in increased blur.

Making Convolutional Networks Shift-Invariant Again

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.