Introduction

2017

Journals

1. Saeeda Naz et al., “UCOM Offline Dataset – An Urdu Handwritten Dataset Generation,” Internation Arab Journal Of Informtion Technology, Volume 14, No. 2, March 2017. (Impact Factor=0.724)
2. Saeeda Naz et al.,“Urdu Nasta'liq Text Recognition System based on Multi-dimensional Recurrent Neural Networks and Statistical Features”, Neural Computing and Application,February 2017, Volume 28, Issue 2, pp 219–231. (JCR 2016/2017 IF: 2.505)
3. Saeeda Naz et al., "Urdu Nastaliq recognition using convolutional–recursive deep learning,"Neuro computing 243, 80–87, 2017. (JCR 2016 IF: 3.317)
4. Saeeda Naz et al., "Extreme learning machine based microscopic red blood cells classification," Cluster Computing, 1-11 (JCR 2017 IF: 2.040)

Conference

1. Saeeda Naz et al., "Deep Learning based Isolated Arabic Scene Character Recognition," Conference: Arabic Script Analysis and Recognition (ASAR), At Nancy, France 1, 2017.
2. Saeeda Naz et al."Automated Techniques for Brain Tumor Segmentation and Detection," The 4th International Conference on Behavioral, Economic, and Socio-Cultural Computing, AGH - University of Science and Technology, Krakow, POLAND / 16-18 October, 2017 .
3. Saeeda Naz et al. "The Impact of Visual Similarities of Arabic-like scripts in Terms of Learning in an OCR System," 6th International Workshop on Multilingual OCR - MOCR 2017 in Kyoto, November 11, 2017.
4. Saeeda Naz et al. "DeepKHATT: A Deep Learning Benchmark on Arabic Script," 6th International Workshop on Multilingual OCR - MOCR 2017 in Kyoto, November 11, 2017.

Book Chapter

Saeeda Naz et al., "Deep Learning for Medical Image Processing: Overview, Challenges and Future," Computer Vision and Pattern Recognition, 2017.

2016

Journals

1. Saeeda Naz et al.,“ Offline cursive Urdu Nastaliq script recognition using Multidimensional Recurrent Neural Networks", in Neurocomputing, Volume 177, 12 February 2016, Pages 228–241. (JCR 2016 IF: 3.317)
2. Saeeda Naz et al.,“Evaluation of Cursive and Non-cursive scripts using Recurrent Neural Networks”, Neural Computing and Applications; DOI:10.1007/s00521-015-1881-4, 27(3), 603-613, 2016. (JCR 2016/2017 IF: 2.505)
3. Saeeda Naz et al.,“Lexicon Reduction for Urdu/Arabic Script Based Character Recognition: A Multilingual OCR", in Mehran University Research Journal of Engineering and Technology, Vol 35, No. 02, April 2016
4. Saeeda Naz et al., "Efficient leukocyte segmentation and recognition in peripheral blood image", in Technology and health care: official journal of the European Society for Engineering and Medicine · February 2016
5. Saeeda Naz et al., "Semi-Automated Transcription Generation for Pashto Cursive Script", Journal of Applied Environmental and Biological Sciences,, January 2016.
6. Saeeda Naz et al., “A Novel Method for Scanning Electron Microscope Image Segmentation and Its Application to Blood Cell Analysis”, Journal of Applied Environmental and Biological Sciences, 2016
7. Saeeda Naz et al., “Efficient Enhancement And Segmentation Of Leukocytes From Microscopic Images”,. Journal of Applied Environmental and Biological Sciences,2016.
8. Saeeda Naz et al. "Efficient leukocyte segmentation and recognition in peripheral blood image," Technology and Health Care (IF: 0.697), (2016)

Book Chapters

1. Saeeda Naz et al., "Balinese Character Recognition Using Bidirectional LSTM Classifier", In book: Lecture Notes in Electrical Engineering (LNEE), Chapter: Balinese Character Recognition Using Bidirectional LSTM Classifier, Publisher: Springer (2016)

2015

Journals

1. Riaz Ahmad, Saeeda Naz, Muhammad Zeeshan Afzal, Hasan Amin, Thomsan Beruel, “Robust Optical Recognition of Cursive Pashto Script using Scale, Rotation and Location Invariant Approach”, PLOS ONE, July 2015. (Impact Factor= 3.534)
2. SaeedaNaz, Arif Iqbal Umar, Muhammad Imran Razzak, “Lexicon reduction for Urdu/Arabic Script Based Character Recognition: A Multilingual Urdu Script OCR”, Mehran University of Engineering & Technology (MUET), (HEC X-category)
3. SaeedaNaz, Arif Iqbal Umar, Muhammad Imran Razzak, “A Hybrid Approach for NER System for Scarce Resourced Language-URDU: Integrating n-gram with Rules and Gazetteers”, Mehran University of Engineering & Technology (MUET), (HEC X-category)
4. SaeedaNaz et al., “Adaptive Filtering Algorithms for Channel Equalization in Wireless Communication”, Indian Journal of Information Technology, 2015. (ISI, ULRICH, SCOPUS)

​Book Chapters

1. Saeeda Naz et al., “Accurate Microscopic Red Blood Cell Image Enhancement and Segmentation”, Bioinformatics and Biomedical Engineering 9043, 183-192, 2015. (LNCS)

2014

Journals

1. Saeeda Naz et al, “The optical character recognition of Urdu-like cursive scripts”, Pattern Recognition 47 (3), 1229-1248, 2014. (JCR 2014 IF: 3.096)
2. Saeeda Naz et al, “Challenges of Urdu Named Entity Recognition: A Scarce Resourced Language”, Research Journal of Applied Sciences, Engineering and Technology 8 (10), 2014. (HEC Y-Category, Indexed In: Ulrich Database, Elsevier (Scopus))
3. Saeeda Naz et al, “The Optical Character Recognition for Cursive Script Using Hmm: A Review,” Research Journal of Applied Sciences, Engineering and Technology 8 (19), 2014. (HEC Y-Category, Indexed In: Ulrich Database, Elsevier (Scopus))
4. Saeeda Naz et al, “Segmentation Techniques for Recognition of Arabic-like Scripts: A Comprehensive Survey,” Education and Information Technologies-Springer, 2015.
5. Saeeda Naz et al, “Statistical Feature Extraction For Urdu Character Using Recurrent Neural Network,”
6. Saeeda Naz et al, "Curvelet based offline analysis of SEM images" PLOS ONE (JCR 2014 IF:4.17)
   

Conference

1. Saeeda Naz et al, "An OCR System For Printed Nasta’liq Script: A Segmentation Based Approach," 17 IEEE International Multi-topic Conference (INMIC), 2014

Book Chapter

1. Saeeda Naz, MI Razzak, K Hayat, MW Anwar, SZ Khan, “Challenges in Baseline Detection of Arabic Script Based Languages”, Intelligent Systems for Science and Information, 181-196, 2014. (LNIS)

2013

Conference

1. Saeeda Naz et al," Challenges in baseline detection of cursive script languages, "Science and Information Conference (SAI), 2013, 551-556, 2013
2. Saeeda Naz et al, "Arabic script based language character recognition: Nasta'liq vs Naskh analysis," Computer and Information Technology (WCCIT), 2013 World Congress on, 1-7
3. Saeeda Naz et al, "Arabic script based character segmentation: A review," Computer and Information Technology (WCCIT), 2013 World Congress on, 1-6

2006

Journals

Saeeda Naz et al. "Mobile IP: enabling user mobility", 2006.