igor3357 commited on
Commit
c9734d0
·
verified ·
1 Parent(s): da0af7c

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +6 -4
README.md CHANGED
@@ -1,6 +1,7 @@
1
  ---
2
  library_name: ultralytics
3
  pipeline_tag: image-segmentation
 
4
  tags:
5
  - YOLO26
6
  - ultralytics
@@ -9,7 +10,6 @@ tags:
9
  - shadowgraph
10
  - fluid-dynamics
11
  - computer-vision
12
- license: apache-2.0
13
  ---
14
 
15
  # YOLO26 Model for Shock-Wave Segmentation
@@ -18,6 +18,8 @@ This repository contains a YOLO26 model for automatic segmentation of shock wave
18
 
19
  The model identifies visible shock-wave structures and returns instance segmentation masks. It is intended for automated processing of high-speed flow-visualization data in gas dynamics and shock-wave experiments.
20
 
 
 
21
  ## Repository Files
22
 
23
  - `shock_seg_model_YOLO26.pt` — trained YOLO26 segmentation model.
@@ -126,6 +128,7 @@ The first frame after alphabetical sorting has index 0. The time unit is user-de
126
  - **Input type:** Experimental shadowgraph images
127
  - **Output:** Shock-wave instance masks
128
  - **Weights:** `shock_seg_model_YOLO26.pt`
 
129
 
130
  ## Limitations
131
 
@@ -138,8 +141,8 @@ Predictions should be validated before the model is used for quantitative measur
138
  If you use the exact model weights or the accompanying script, please cite this model repository:
139
 
140
  ```bibtex
141
- @misc{doroshchenko2026shockwaveyolo26,
142
- author = {Doroshchenko, Igor A.},
143
  title = {YOLO26 Model for Shock-Wave Segmentation},
144
  year = {2026},
145
  publisher = {Hugging Face},
@@ -197,4 +200,3 @@ This article is the most directly relevant methodological reference for automati
197
  ```
198
 
199
  For work focused specifically on the released YOLO26 weights, cite the model repository. For broader methodological and physical context, cite the most relevant publication above in addition to the repository.
200
-
 
1
  ---
2
  library_name: ultralytics
3
  pipeline_tag: image-segmentation
4
+ license: apache-2.0
5
  tags:
6
  - YOLO26
7
  - ultralytics
 
10
  - shadowgraph
11
  - fluid-dynamics
12
  - computer-vision
 
13
  ---
14
 
15
  # YOLO26 Model for Shock-Wave Segmentation
 
18
 
19
  The model identifies visible shock-wave structures and returns instance segmentation masks. It is intended for automated processing of high-speed flow-visualization data in gas dynamics and shock-wave experiments.
20
 
21
+ **Model authors:** Igor Doroshchenko, Pavel Popov, Aleksei Moiseevskii, and Tahir Kuli-Zade.
22
+
23
  ## Repository Files
24
 
25
  - `shock_seg_model_YOLO26.pt` — trained YOLO26 segmentation model.
 
128
  - **Input type:** Experimental shadowgraph images
129
  - **Output:** Shock-wave instance masks
130
  - **Weights:** `shock_seg_model_YOLO26.pt`
131
+ - **Authors:** Igor Doroshchenko, Pavel Popov, Aleksei Moiseevskii, and Tahir Kuli-Zade
132
 
133
  ## Limitations
134
 
 
141
  If you use the exact model weights or the accompanying script, please cite this model repository:
142
 
143
  ```bibtex
144
+ @misc{doroshchenkoEtAl2026shockwaveyolo26,
145
+ author = {Doroshchenko, Igor and Popov, Pavel and Moiseevskii, Aleksei and Kuli-Zade, Tahir},
146
  title = {YOLO26 Model for Shock-Wave Segmentation},
147
  year = {2026},
148
  publisher = {Hugging Face},
 
200
  ```
201
 
202
  For work focused specifically on the released YOLO26 weights, cite the model repository. For broader methodological and physical context, cite the most relevant publication above in addition to the repository.