edit README.md
Browse files
README.md
CHANGED
@@ -13,10 +13,10 @@ tags:
|
|
13 |
## Introduction
|
14 |
**EXAONE Path for CRCMSI** is an **enhanced whole-slide image (WSI) classification framework** that retains the core architecture of EXAONE Path 1.5 while upgrading its internals for greater efficiency and richer multimodal integration.
|
15 |
|
16 |
-
The pipeline still unfolds in two stages:
|
17 |
-
|
18 |
-
1. **Patch-wise feature extraction** – Each WSI is tiled into 256 × 256 px patches, which are embedded into 768-dimensional vectors using the frozen **[EXAONE Path v1.0](https://huggingface.co/LGAI-EXAONE/EXAONEPath)** encoder.
|
19 |
-
2. **Slide-level aggregation** – The patch embeddings are aggregated using a Vision Transformer, producing a unified slide-level representation that a lightweight classification head transforms into task-specific probabilities.
|
20 |
|
21 |
---
|
22 |
|
|
|
13 |
## Introduction
|
14 |
**EXAONE Path for CRCMSI** is an **enhanced whole-slide image (WSI) classification framework** that retains the core architecture of EXAONE Path 1.5 while upgrading its internals for greater efficiency and richer multimodal integration.
|
15 |
|
16 |
+
The pipeline still unfolds in two stages:
|
17 |
+
|
18 |
+
1. **Patch-wise feature extraction** – Each WSI is tiled into 256 × 256 px patches, which are embedded into 768-dimensional vectors using the frozen **[EXAONE Path v1.0](https://huggingface.co/LGAI-EXAONE/EXAONEPath)** encoder.
|
19 |
+
2. **Slide-level aggregation** – The patch embeddings are aggregated using a Vision Transformer, producing a unified slide-level representation that a lightweight classification head transforms into task-specific probabilities.
|
20 |
|
21 |
---
|
22 |
|