Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: cc-by-4.0
+task_categories:
+- image-classification
+language:
+- en
+pretty_name: >-
+  Mobile-Scanned Handwritten Examination Answer Scripts Image Classification
+  Dataset
+size_categories:
+- 1K<n<10K
+---
+<h1 align="center" class="big-title">
+  <span style="color:green; font-size:40px;">🧑‍🎓✏️📚 Student Handwritten Exam Dataset🧑‍🎓✏️📚 </span><br>
+</h1>
+<img src="https://huggingface.co/datasets/chandrabhuma/AnswerScripts/resolve/main/BECLogo.jpg" 
+     alt="LOGO" width="150" 
+     style="display:block; margin-left:auto; margin-right:auto;"/>
+
+
+## 📌 Dataset Summary
+
+This dataset contains **real-world handwritten examination answer scripts** collected from **21 students**, scanned using **mobile phone cameras**. The images were manually organized into **21 class folders**, corresponding to individual students.  
+
+The dataset includes **5,914 images**, all resized to **224×224 pixels**, and contains **natural variations such as rotation and flipping**, making it suitable for training **robust document image classification and recognition models**.
+
+This dataset is intended for research and development in:
+
+✍️ Handwriting-Based Biometric Identification
+
+🎯 Writer Identification
+
+🤖 Image Classification
+
+
+---
+
+## 📊 Dataset Statistics
+
+| Property | Value |
+|-----------|--------|
+| Total Students (Classes) | 21 |
+| Total Images | 5,914 |
+| Image Resolution | 224 × 224 |
+| Image Type | RGB |
+| Acquisition Method | Mobile Phone Scanning |
+| Task Type | Image Classification |
+| Dataset Structure | Folder-wise class labels |
+
+---
+
+## 📁 Dataset Structure
+
+
+Each folder corresponds to **one student**, and contains scanned handwritten answer script images belonging to that student.
+
+---
+
+## 🖼️ Nature of  Images
+
+> The dataset includes diverse handwriting styles, variations in lighting, orientation, and background, providing realistic challenges for machine learning models.
+
+---
+
+## 🎯 Intended Use
+
+This dataset is suitable for:
+
+- Handwritten document image classification  
+- Student-wise handwriting identification  
+- Document image preprocessing research  
+- OCR pipeline development  
+- Deep learning model benchmarking  
+
+---
+
+## ⚠️ Limitations
+
+- Dataset size is moderate (≈6K images).
+- Images were captured using mobile devices, so lighting and perspective variations exist.
+- No word-level or character-level annotations are provided.
+
+---
+
+## 🧾 License
+
+This dataset is released under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license.
+
+You are free to:
+
+- Share  
+- Adapt  
+- Use commercially  
+
+**with proper attribution.**
+
+---
+
+## 👥 Contributors
+
+- **Chandra Mohan Bhuma** (Professor, Dept of ECE, Bapatla Engineering College, Bapatla)
+- — 📧 chandrabhuma@gmail.com  
+- **Mahaboob Subani Shaik**(Asst.Professor, Dept of ECE, Bapatla Engineering College, Bapatla)
+- — 📧 skmsubanibec@gmail.com  
+- **Gundreddy Dhatri**(UG Student, Dept of ECE, Bapatla Engineering College, Bapatla)
+-  — 📧 gundreddydhatri@gmail.com  
+- **Munagala Gowtham**(UG Student, Dept of ECE, Bapatla Engineering College, Bapatla)
+- — 📧 munagalagowtham130@gmail.com  
+- **Motupalli Dinesh Kumar**(UG Student, Dept of ECE, Bapatla Engineering College, Bapatla)
+-  — 📧 dineshmotupalli44@gmail.com  
+- **Molathoti David Living Stone**(UG Student, Dept of ECE, Bapatla Engineering College, Bapatla)
+-  — 📧 davidlivingstone200308@gmail.com  
+
+---
+
+## 📣 Citation
+
+If you use this dataset in your research, please cite as:
+
+@dataset{handwritten_exam_scripts_2026,
+title = {Student Handwritten Exam Dataset},
+author = {Chandra Mohan B, Subani, Sk. M. and Dhatri, Gundreddy and Gowtham, Munagala and Dinesh Kumar, Motupalli and David Living Stone, Molathoti},
+year = {2026},
+publisher = {Hugging Face},
+url = {https://huggingface.co/datasets/
+<your-username>/<dataset-name>}
+}