**ScanSSD** is a single-shot Detector ([SSD](https://paperswithcode.com/method/ssd)) for locating math formulas offset from text and embedded in textlines. It uses only visual features for detection: no formatting or typesetting information such as layout, font, or character labels are employed. Given a 600 dpi document page image, a Single Shot Detector (SSD) locates formulas at multiple scales using sliding windows, after which candidate detections are pooled to obtain page-level results.

Scalable method to train large scale GNN models via sampling small subgraphs.

GraphSAINT

GraphSAINT: Graph Sampling Based Inductive Learning Method

ScanSSD

ScanSSD: Scanning Single Shot Detector for Mathematical Formulas in PDF Document Images

A **SENet** is a convolutional neural network architecture that employs squeeze-and-excitation blocks to enable the network to perform dynamic channel-wise feature recalibration.

Source	ScanSSD: Scanning Single Shot Detector for Mathematical Formulas in PDF Document Images
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com