Computer Science & Engineering

Research Activity

The present research areas of the department are as follows  
  • Image Processing,
  • Machine Learning,
  • Pattern Recognition,
  • Robotics,
  • VLSI,
  • Computer Architecture


Ghosh, S., Hassan, S. K., Khan, A. H., Manna, A., Bhowmik, S., & Sarkar, R. (2021). Application of texture-based features for text non-text classification in printed document images with novel feature selection algorithm. Soft Computing, 1-19. DOI:[SCI]

Mondal, R., Bhowmik, S., & Sarkar, R. (2020). “tsegGAN: A Generative Adversarial Network for Segmenting Touching Nontext Components From Text Ones in Handwriting”. IEEE Transactions on Instrumentation and Measurement70, 1-10. DOI: 10.1109/TIM.2020.3038277. [SCI] 

Basu, A., Mondal, R., Bhowmik, S., & Sarkar, R. (2020). U-Net versus Pix2Pix: a comparative study on degraded document image binarization. Journal of Electronic Imaging, 29(6), 063019. [SCI]

Bhowmik, S., Kundu, S., & Sarkar, R. (2020). BINYAS: a complex document layout analysis system. Multimedia Tools and Applications, 1-34, DOI: .[SCI]

Malakar, S., Ghosh, M., Chaterjee, A., Bhowmik, S., & Sarkar, R. (2020). Offline music symbol recognition using Daisy feature and quantum Grey wolf optimization based feature selection. Multimedia Tools and Applications79(43), 32011-32036. [SCI]

Bera, S. K., Ghosh, S., Bhowmik, S., Sarkar, R., & Nasipuri, M. (2020). A non-parametric binarization method based on ensemble of clustering algorithms. Multimedia Tools and Applications, 1-21. DOI: [SCI]

Bhattacharya, R., Malakar, S., Ghosh, S., Bhowmik, S., & Sarkar, R. Understanding contents of filled-in Bangla form images. Multimedia Tools and Applications, 803529–3570 (2021). [SCI]

 Ghosh, M., Ghosh, K.K., Bhowmik, S. Sarkar, R. Coalition game based feature selection for text non-text separation in handwritten documents using LBP based features. Multimed Tools Appl 80, 3229–3249 (2021). DOI: [SCI]

Ghosh, S., Chatterjee, A., Singh, P. K., Bhowmik, S., & Sarkar, R. (2020). Language-invariant novel feature descriptors for handwritten numeral recognition. The Visual Computer, 1-23. DOI: [SCI]

Malakar, S., Paul, S., Kundu, S., Bhowmik, S., Sarkar, R., & Nasipuri, M. (2020). Handwritten word recognition using lottery ticket hypothesis based pruned            CNN model: a new benchmark on CMATERdb2. 1.2. Neural Computing and Applications, 32(18), 15209-15220. [SCI] 

Bhowmik, S., & Sarkar, R. (2020, October). Classification of Text regions in a Document Image by Analyzing the properties of Connected Components. In               2020 IEEE Applied Signal Processing Conference (ASPCON) (pp. 36-40). IEEE.

 Guha, R., Ghosh, K. K., Bhowmik, S., & Sarkar, R. (2020, February). Mutually Informed Correlation Coefficient (MICC)-a New Filter Based Feature                        Selection Method. In 2020 IEEE Calcutta Conference (CALCON) (pp. 54-58). IEEE.

Mukhopadhyay, K., Bose, R., Mondal, A., Bera, S. K., Bhowmik, S., & Sarkar, R. (2020, February). Removal of Salt and Pepper noise: A Game Theoretic                  Approach. In 2020 IEEE Calcutta Conference (CALCON) (pp. 122-126). IEEE.