Acc: 88.95
Papers with Code · CC BY-SA 4.0
Image Classification
Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.
<span class="description-source">Source: Metamorphic Testing for Object Detection Systems </span>
개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.
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데이터셋
505개논문
Accuracy: 98.56Precision: 99.94F1-Score: 99.24
Accuracy: 98.59Precision: 99.94F1-Score: 99.25
Accuracy: 98.74Precision: 99.97F1-Score: 99.38
Accuracy: 96.90Precision: 99.91F1-Score: 98.38
Accuracy: 98.11Precision: 99.94F1-Score: 99.01
Accuracy: 97.48Precision: 99.97F1-Score: 98.70
Accuracy: 98.68Precision: 99.91F1-Score: 99.29
라이브러리
Papers with Code 리더보드 row에 연결된 구현 저장소입니다.
하위 태스크
FI
Few-Shot Image Classification
SI
Semi-Supervised Image Classification
FI
Fine-Grained Image Classification
SI
Self-Supervised Image Classification
LW
Learning with noisy labels
HI
Hyperspectral Image Classification
EV
Efficient ViTs
UI
Unsupervised Image Classification
SI
Sequential Image Classification
DI
Document Image Classification
SD
Small Data Image Classification
MI
Multi-Label Image Classification