Automated Author Profile

Chavan, Snehal

Annasaheb Dange College of Engineering and Technology

Current S-Index

6.0

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.5

Average Dataset Index per dataset

Total Datasets

4

Total datasets for this author

Average FAIR Score

65.4%

Average FAIR Score per dataset

Total Citations

1

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

GVLiD: GrapeVine Leaf identification of the Diseases

Grapes are one of the most important crops in global agriculture, primarily used for wine, fresh fruit, and raisins. Nevertheless, grapevines are prone to various diseases that can significantly impact their yield and quality. Early detection and treatment of these diseases is essential.We introduce the "GVLiD: GrapeVine Leaf identification of the Diseases" which has 4 classes of 3,477 high resolution images of grape leaves; nine diseased classes and one healthy leaves class. The dataset covers the following common grapevine diseases:1) Healthy2) Black rot3) Esca4) Leaf blightThe dimension of the images is 1080 X 1080. Images are in JPG format. Images having 120 DPI collected through a field visit and captured from different angles.

Authors

  • Shikalgar, Anisa ;
  • Savalkar, Ayush ;
  • Bhasme, Avishkar ;
  • Chavan, Snehal ;
  • Nikam, Vaishnavi
0 Citations0 Mentions65% FAIR1.6 Dataset Index
10.17632/wkymf8bhcgSeptember 2025

GVLiD: GrapeVine Leaf identification of the Diseases

Grapes are one of the most important crops in global agriculture, primarily used for wine, fresh fruit, and raisins. Nevertheless, grapevines are prone to various diseases that can significantly impact their yield and quality. Early detection and treatment of these diseases is essential.We introduce the "GVLiD: GrapeVine Leaf identification of the Diseases" which has 4 classes of 3,477 high resolution images of grape leaves; nine diseased classes and one healthy leaves class. The dataset covers the following common grapevine diseases:1) Healthy2) Black rot3) Esca4) Leaf blightThe dimension of the images is 1080 X 1080. Images are in JPG format. Images having 120 DPI collected through a field visit and captured from different angles.

Authors

  • Shikalgar, Anisa ;
  • Savalkar, Ayush ;
  • Bhasme, Avishkar ;
  • Chavan, Snehal ;
  • Nikam, Vaishnavi
0 Citations0 Mentions65% FAIR1.6 Dataset Index
10.17632/wkymf8bhcg.3September 2025

Grape Disease

Grapes are one of the most important crops in the global agriculture, as they are mainly used for wine, fresh fruit, and raisins. Nevertheless, grapevines are prone to various diseases which can significantly impact their yield and quality. Early detection and treatment of these diseases is important.We introduce the "Grape Leaf Dataset" which has 4 classes of 3,477 high resolution images of grape leaves; nine diseased classes and one healthy leaves class. The dataset covers the following common grapevine diseases:1) Healthy2) Black rot3) Esca4) Leaf blightThe dimension of the images is 1080 X 1080. Images are in JPG format. Images having 120 DPI collected through field visit and capturing from different angles.

Authors

  • Shikalgar, Anisa ;
  • Savalkar, Ayush ;
  • Bhasme, Avishkar ;
  • Chavan, Snehal ;
  • Nikam, Vaishnavi
0 Citations0 Mentions65% FAIR1.6 Dataset Index
10.17632/wkymf8bhcg.2August 2025

Grape Disease

Grapes are one of the most important crops in the global agriculture, as they are mainly used for wine, fresh fruit, and raisins. Nevertheless, grapevines are prone to various diseases which can significantly impact their yield and quality. Early detection and treatment of these diseases is important.We introduce the "Grape Leaf Dataset" which has 4 classes of 3,477 high resolution images of grape leaves; nine diseased classes and one healthy leaves class. The dataset covers the following common grapevine diseases:1) Healthy2) Black rot3) Esca4) Leaf blightThe dimension of the images is 1080 X 1080. Images are in JPG format. Images having 120 DPI collected through field visit and capturing from different angles.

Authors

  • Shikalgar, Anisa ;
  • Savalkar, Ayush ;
  • Bhasme, Avishkar ;
  • Chavan, Snehal ;
  • Nikam, Vaishnavi
1 Citation0 Mentions65% FAIR1.1 Dataset Index
10.17632/wkymf8bhcg.1December 2024