Dr. Latika Pinjarkar obtained a BE degree in Computer Technology from Nagpur University, MH in 1999 and an M. Tech degree in Computer Technology and Application from CSVTU, CG, India in 2008. She obtained her Ph.D. in Computer Science and Engineering from CSVTU CG, India in 2019. She has been engaged in research and teaching for more than 22 years. At present, she is an Associate Professor and Academic Head in the CSE Department at Symbiosis Institute of Technology Nagpur, Symbiosis International (Deemed University) Pune, MH, India.
She has presented more than 50 papers in International/National Journals/ Conferences and has 05 Patents to her credit. She has completed one research project sponsored by TEQIP-III. Her research interests include Image Processing, Computer Vision, Content-Based Image Retrieval(CBIR) and Machine Learning.
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1 | L. Pinjarkar, et al., Denoising of Digital Images Using Spatial Domain Edge Detection Approach, International Journal of Religion, 2024, Volume 5, Issue 6, Pages 298 – 307, DOI:10.61707/y562qn51 |
2 | L. Pinjarkar, et al., Forecasting Stellar XLM Prices: Insights from ARIMA Analysis, International Journal of Religion, 2024, Volume 5, Issue 6, Pages 273 – 288, DOI:10.61707/7074ja52 |
3 | L. Pinjarkar et al., “Social Media in the Digital Age: A Comprehensive Review of Impacts, Challenges and Cybercrime,” Engineering Proceedings, March 2024. |
4 | L. Pinjarkar et al., “A Comprehensive Review of Metaverse: Taxonomy, Impact, and the Hype around It,” Engineering Proceedings, March 2024. |
5 | L. Pinjarkar et al., “Predictive Modeling of Bitcoin Prices using Machine Learning Techniques,” International Journal of Intelligent Systems and Applications in Engineering (IJISAE), Feb 2024. |
6 | L. Pinjarkar et al., “Enhanced Power Quality and Forecasting for PV-Wind Microgrid Using Proactive Shunt Power Filter and Neural Network-Based Time Series Forecasting” Electric Power Components and Systems, publisher: Taylor & Francis, DOI: 10.1080/15325008.2023.2249894, Published online: 06 Sep 2023 |
7 | L. Pinjarkar et al., “Improved System for Retrieval of Color Logo Images using PSO, SOM and Relevance Feedback Technique”. IT in Industry, Vol. 9, No.1, 2021, ISSN (Online) 2203-17 31,ISSN (Print) 2204- 0595, Published Online 10-03-2021 DOI: https://doi.org/10.17762/itii.v9i1.181 |
8 | L. Pinjarkar et al., “Deep CNN combined with Relevance Feedback for Trademark Image Retrieval” 2018. Journal of Intelligent Systems, Journal of Intelligent Systems. 20180083, ISSN (Online) 2191-026X, ISSN (Print) 0334-1860, Published Online:2018-09-15, DOI: https://doi.org/10.1515/jisys-2018-0083. |
9 | L. Pinjarkar et al., “Content-Based Image Retrieval using Deep Learning: A Comprehensive Survey” MARCH/2018.International Journal of Management, Technology and Engineering (IJMTE) ISSN NO:2249-7455.DOI: 16.10089.IJAMTES.2018.V8I03.15.43653.8(III):567-572. |
10 | L. Pinjarkar et al., “Novel Relevance Feedback Approach for Color Trademark Recognition Using optimization and Learning Strategy” 2018.Journal of Intelligent Systems, ISSN: 2191-026X DOI: 10.1515/jisys-2017-0022. 27(1): 67–79. |
11 | L. Pinjarkar et al., “Novel System for Color Logo Recognition Using Optimization and Learning Based Relevance Feedback Technique” October-December 2017. International Journal of Computer Vision and Image Processing (IJCVIP) (IGI GLOBAL). ISSN: 2155-6997 EISSN: 2155-6989. DOI: 0.4018/IJCVIP.2017100103. 7(4):PP.28-40. |
12 | L. Pinjarkar et al., “Comparison and Analysis of Content Based Image Retrieval Systems Based on Relevance Feedback” July 2012. Journal of Emerging Trends in Computing and Information Sciences (CIS Journal). ISSN 2079- 8407.3(6): 833-837. |
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1 | L. Pinjarkar et al., “Comparison and Analysis of Trademark Image Retrieval Systems” August 13-14, 2016.International Conference on Cyber Security (ICCS 2016), Rajasthan Technical University, Kota. |
2 | L. Pinjarkar et al., “Improved Trademark Image Retrieval System using Relevance Feedback” December 23- 25, 2016. 8thInternational Conference on Computational Intelligence and Communication Networks (CICN IEEE). MIR Labs Chapter Jabalpur, India. DOI 10.1109/CICN.2016.65 :298-304. |
3 | L. Pinjarkar et al., “Efficient System for Color Logo Recognition based on Self-Organizing Map and Relevance Feedback technique” March 3-4 2017. 1st International Conference on Smart Computing and Informatics (SCI- 2017), Visakhapatnam, India. Smart Computing and Informatics, Smart Innovation, Systems and Technologies 77, Springer Publisher, https://doi.org/10.1007/978-981-10-5544-7_6 53-62 |
4 | L. Pinjarkar, et al., New algorithms and technologies for data mining, Data Mining and Machine Learning Applications, Pages 365 – 395, DOI:10.1002/9781119792529.ch14 |
5 | L. Pinjarkar, et al., Latest advancement in automotive embedded system using IoT computerization, Green Computing and Its Applications, 2021, Pages 131 – 165, ISBN:978-168507363-3, 978-168507357-2 |
6 | L. Pinjarkar, et al., Advancement in augmented and virtual reality, Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms, 2021, Pages 211 – 240, DOI:10.1002/9781119792109.ch10 |
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1 | Detection of Cardiac Arrest by using Network Intrusion Detection System: Published Application number: 202221034061 A by Indian Government Date of Publication 01/July/2022. |
2 | Multilingual Speaker Identification System: Published Application number: 202221032172 A by Indian Government Date of Publication 24/June/2022. |
3 | A System for Intensity Based Distinctive Feature Extraction and Matching for Sign Language: Published Application number: 202221032805 A by Indian Government Date of Publication 24/June/2022. |
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