Papers with Code 아카이브

Cell Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
4
보존된 평가 기록
7

Cell Detection

기법

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

CPN

The Contour Proposal Network (CPN) detects possibly overlapping objects in an image while simultaneously fitting pixel-precise closed object contours. The CPN can incorporate state of the art object detection architectures as backbone networks into a fast single-stage instance segmentation model that can be trained end-to-end.

Contour Proposal Networks for Biomedical Instance Segmentation

TABBIE

TABBIE is a pretraining objective (corrupt cell detection) that learns exclusively from tabular data. Unlike other approaches, TABBIE provides embeddings of all table substructures (cells, rows, and columns). TABBIE can be seen as a table embedding model trained to detect corrupted cells, inspired by the ELECTRA objective function.

TABBIE: Pretrained Representations of Tabular Data

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