Hewan Shrestha

@uni-saarland.de

Visual Computing
Saarland University

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Vision and Pattern Recognition, Global and Planetary Change, Artificial Intelligence
5

Scopus Publications

103

Scholar Citations

6

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Detection and classification of dermatoscopic images using segmentation and transfer learning
    Hewan Shrestha, Subash Chandra Bose Jaganathan, Chandramohan Dhasarathan, Kannadhasan Suriyan
    Multimedia Tools and Applications, 2023
  • Face Mask Recognition Based on Two-Stage Detector
    Hewan Shrestha, Swati Megha, Subham Chakraborty, Manuel Mazzara, Iouri Kotorov
    Lecture Notes in Networks and Systems, 2023
  • Recent advances in Edge computing paradigms: Taxonomy benchmarks and standards for unconventional computing
    Sana Sodanapalli, Hewan Shrestha, Chandramohan Dhasarathan, Puviyarasi T., Sam Goundar
    Research Anthology on Edge Computing Protocols Applications and Integration, 2022
    Edge computing is an exciting new approach to network architecture that helps organizations break beyond the limitations imposed by traditional cloud-based networks. It has emerged as a viable and important architecture that supports distributed computing to deploy compute and storage resources closer to the data source. Edge and fog computing addresses three principles of network limitations of bandwidth, latency, congestion, and reliability. The research community sees edge computing at manufacturing, farming, network optimization, workplace safety, improved healthcare, transportation, etc. The promise of this technology will be realized through addressing new research challenges in the IoT paradigm and the design of highly-efficient communication technology with minimum cost and effort.
  • An NLP Based Sentimental Analysis and Prediction: A Dynamic Approach
    Chandramohan Dhasarathan, Hewan Shrestha
    Communications in Computer and Information Science, 2021
  • Natural Language Processing Based Sentimental Analysis of Hindi (SAH) Script an Optimization Approach
    Hewan Shrestha, Chandramohan Dhasarathan, Shanmugam Munisamy, Amudhavel Jayavel
    International Journal of Speech Technology, 2020
    Sentimental analysis is one of the most common applications of Natural Language Processing (NLP). Sentiment analysis, the term itself refers to identify the emotions and opinions of people through written text. It is concerned with information extraction from any text based on the polarity in social behavior whether it may be positive, negative or neutral. This paper presents a practical dynamic approach on to find the polarity of any sentence and analyse the opinion of the particular sentence. The proposed Sentimental Analysis of Hindi (SAH) script have adopted two different classifier Naïve Bayes Classifier and Decision Tree Classifier is used for the text extraction. The positive, neutral and negative result validation shows a comparative result of sentimental analysis.

RECENT SCHOLAR PUBLICATIONS

  • A Weak Supervision Learning Approach Towards an Equitable Mobility Estimation
    T Aidoo, T Koebe, A Maurya, H Shrestha, I Weber
    Workshop Proceedings of the 19th International AAAI Conference on Web and … , 2025
    2025
  • Self-Supervision in Time for Satellite Images (S3-TSS): A novel method of SSL technique in Satellite images
    A Maurya, H Shrestha, MM Shahriar
    arXiv preprint arXiv:2403.04859 , 2024
    2024
  • LLMRS: Unlocking potentials of LLM-based recommender systems for software purchase
    A John, T Aidoo, H Behmanush, IB Gunduz, H Shrestha, MR Rahman, ...
    arXiv preprint arXiv:2401.06676 , 2024
    2024
    Citations: 7
  • Detection and classification of dermatoscopic images using segmentation and transfer learning
    H Shrestha, SCB Jaganathan, C Dhasarathan, K Suriyan
    Multimedia Tools and Applications 82 (15), 23817-23831 , 2023
    2023
    Citations: 15
  • Face mask recognition based on two-stage detector
    H Shrestha, S Megha, S Chakraborty, M Mazzara, I Kotorov
    International Conference on Intelligent Systems Design and Applications, 576-585 , 2022
    2022
    Citations: 17
  • A deep learning based convolution neural network-DCNN approach to detect brain tumor
    H Shrestha, C Dhasarathan, M Kumar, R Nidhya, A Shankar, M Kumar
    Proceedings of Academia-Industry Consortium for Data Science: AICDS 2020 … , 2022
    2022
    Citations: 17
  • Recent advances in edge computing paradigms: Taxonomy benchmarks and standards for unconventional computing
    S Sodanapalli, H Shrestha, C Dhasarathan, S Goundar
    Research Anthology on Edge Computing Protocols, Applications, and … , 2022
    2022
    Citations: 2
  • Evolution of fog computing applications, opportunities, and challenges: A systematic review
    H Shrestha, T Puviyarai, S Sodanapalli, C Dhasarathan
    International Journal of Fog Computing (IJFC) 4 (1), 1-17 , 2021
    2021
    Citations: 3
  • An NLP based sentimental analysis and prediction: a dynamic approach
    C Dhasarathan, H Shrestha
    International Conference on Communication, Networks and Computing, 343-353 , 2020
    2020
    Citations: 7
  • Natural language processing based sentimental analysis of Hindi (SAH) script an optimization approach
    H Shrestha, C Dhasarathan, S Munisamy, A Jayavel
    International Journal of Speech Technology 23 (4), 757-766 , 2020
    2020
    Citations: 35

MOST CITED SCHOLAR PUBLICATIONS

  • Natural language processing based sentimental analysis of Hindi (SAH) script an optimization approach
    H Shrestha, C Dhasarathan, S Munisamy, A Jayavel
    International Journal of Speech Technology 23 (4), 757-766 , 2020
    2020
    Citations: 35
  • Face mask recognition based on two-stage detector
    H Shrestha, S Megha, S Chakraborty, M Mazzara, I Kotorov
    International Conference on Intelligent Systems Design and Applications, 576-585 , 2022
    2022
    Citations: 17
  • A deep learning based convolution neural network-DCNN approach to detect brain tumor
    H Shrestha, C Dhasarathan, M Kumar, R Nidhya, A Shankar, M Kumar
    Proceedings of Academia-Industry Consortium for Data Science: AICDS 2020 … , 2022
    2022
    Citations: 17
  • Detection and classification of dermatoscopic images using segmentation and transfer learning
    H Shrestha, SCB Jaganathan, C Dhasarathan, K Suriyan
    Multimedia Tools and Applications 82 (15), 23817-23831 , 2023
    2023
    Citations: 15
  • LLMRS: Unlocking potentials of LLM-based recommender systems for software purchase
    A John, T Aidoo, H Behmanush, IB Gunduz, H Shrestha, MR Rahman, ...
    arXiv preprint arXiv:2401.06676 , 2024
    2024
    Citations: 7
  • An NLP based sentimental analysis and prediction: a dynamic approach
    C Dhasarathan, H Shrestha
    International Conference on Communication, Networks and Computing, 343-353 , 2020
    2020
    Citations: 7
  • Evolution of fog computing applications, opportunities, and challenges: A systematic review
    H Shrestha, T Puviyarai, S Sodanapalli, C Dhasarathan
    International Journal of Fog Computing (IJFC) 4 (1), 1-17 , 2021
    2021
    Citations: 3
  • Recent advances in edge computing paradigms: Taxonomy benchmarks and standards for unconventional computing
    S Sodanapalli, H Shrestha, C Dhasarathan, S Goundar
    Research Anthology on Edge Computing Protocols, Applications, and … , 2022
    2022
    Citations: 2
  • A Weak Supervision Learning Approach Towards an Equitable Mobility Estimation
    T Aidoo, T Koebe, A Maurya, H Shrestha, I Weber
    Workshop Proceedings of the 19th International AAAI Conference on Web and … , 2025
    2025
  • Self-Supervision in Time for Satellite Images (S3-TSS): A novel method of SSL technique in Satellite images
    A Maurya, H Shrestha, MM Shahriar
    arXiv preprint arXiv:2403.04859 , 2024
    2024