Automated Author ProfileHimel, Galib Muhammad Shahriar
American International University Bangladesh
Himel, Galib Muhammad Shahriar
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 4.9 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset is divided into 3 parts; Each part consists of smooth luffa grading, diseases, and flowers respectively. These images were captured from different village fields of Faridpur, Bangladesh. To construct the dataset, we have considered Luffa Aegyptiaca commonly known as Smooth Luffa (Dhundal/ধুন্দল). This dataset consists of a total of 1,933 JPG images; the dimension of each image is 1728 x 1728 pixels. The total size of the dataset is 1.45 GB. The dataset contains 3 folders: Luffa_Diseases, Flowers, and Luffa_Grade. The detail of the dataset:• Luffa_Diseases: This dataset contains leaves of smooth luffa representing various diseases along with non-affected ones. The categories of this dataset are Alternaria Disease, Angular Spot Disease, Holed Leaves, Mosaic Virus, and Fresh Leaves. A total of 1,228 JPG raw images are presented in this folder.• Flowers: This dataset contains flowers of smooth luffa. There is only a single category of this dataset. A total of 362 JPG raw images are presented in this folder. These images represent various maturity stages of smooth luffa flowers. • Luffa_Grade: This dataset contains fresh and defective smooth luffa. The categories of this dataset are Fresh and Faulty Luffa. A total of 343 JPG raw images are presented in this folder.--------------------For Computer Vision Purpose we have uploaded a pre-processed and more CV friendly dataset version "Luffa_Disease_FINAL.zip" which contains TRAIN (5000 images by augmenting) and TEST (500 unique images) without overlapping any dataset among Train and Test. Image size is uniformed (256x256).
Authors
- Islam, Md Masudul ;
- Sheikh, Md Ripon ;
- Himel, Galib Muhammad Shahriar
This dataset is divided into 3 parts; Each part consists of smooth luffa grading, diseases, and flowers respectively. These images were captured from different village fields of Faridpur, Bangladesh. To construct the dataset, we have considered Luffa Aegyptiaca commonly known as Smooth Luffa (Dhundal/ধুন্দল). This dataset consists of a total of 1,933 JPG images; the dimension of each image is 1728 x 1728 pixels. The total size of the dataset is 1.45 GB. The dataset contains 3 folders: Luffa_Diseases, Flowers, and Luffa_Grade. The detail of the dataset:• Luffa_Diseases: This dataset contains leaves of smooth luffa representing various diseases along with non-affected ones. The categories of this dataset are Alternaria Disease, Angular Spot Disease, Holed Leaves, Mosaic Virus, and Fresh Leaves. A total of 1,228 JPG raw images are presented in this folder.• Flowers: This dataset contains flowers of smooth luffa. There is only a single category of this dataset. A total of 362 JPG raw images are presented in this folder. These images represent various maturity stages of smooth luffa flowers. • Luffa_Grade: This dataset contains fresh and defective smooth luffa. The categories of this dataset are Fresh and Faulty Luffa. A total of 343 JPG raw images are presented in this folder.--------------------For Computer Vision Purpose we have uploaded a pre-processed and more CV friendly dataset version "Luffa_Disease_FINAL.zip" which contains TRAIN (5000 images by augmenting) and TEST (500 unique images) without overlapping any dataset among Train and Test. Image size is uniformed (256x256).
Authors
- Islam, Md Masudul ;
- Sheikh, Md Ripon ;
- Himel, Galib Muhammad Shahriar
This dataset is divided into 3 parts; Each part consists of smooth luffa grading, diseases, and flowers respectively. These images were captured from different village fields of Faridpur, Bangladesh. To construct the dataset, we have considered Luffa Aegyptiaca commonly known as Smooth Luffa (Dhundal/ধুন্দল). This dataset consists of a total of 1,933 JPG images; the dimension of each image is 1728 x 1728 pixels. The total size of the dataset is 1.45 GB. The dataset contains 3 folders: Luffa_Diseases, Flowers, and Luffa_Grade. The detail of the dataset:• Luffa_Diseases: This dataset contains leaves of smooth luffa representing various diseases along with non-affected ones. The categories of this dataset are Alternaria Disease, Angular Spot Disease, Holed Leaves, Mosaic Virus, and Fresh Leaves. A total of 1,228 JPG raw images are presented in this folder.• Flowers: This dataset contains flowers of smooth luffa. There is only a single category of this dataset. A total of 362 JPG raw images are presented in this folder. These images represent various maturity stages of smooth luffa flowers. • Luffa_Grade: This dataset contains fresh and defective smooth luffa. The categories of this dataset are Fresh and Faulty Luffa. A total of 343 JPG raw images are presented in this folder.We have also uploaded a Resized version (224 X 224 pixels) of full dataset in zip format.---------------------------------------------------------------Another version of this dataset is [Luffa Leaves Diseases] is given in zip format named: "Luffa_Diseases_REAL.zip"Train dataset contains 4000 images (800 original+augmented images each class)Train dataset contains 500 images (100 original and non-overlapped images each class)
Authors
- Islam, Md Masudul ;
- Sheikh, Md Ripon ;
- Himel, Galib Muhammad Shahriar