Yogesh Kumar

ORCID: 0009-0009-4363-5317
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About
Contact & Profiles
Research Areas
  • Advanced Image and Video Retrieval Techniques
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Regional Development and Management Studies
  • Human Resource Development and Performance Evaluation
  • Image and Signal Denoising Methods
  • Business and Economic Development
  • Topic Modeling
  • Video Analysis and Summarization
  • Organizational and Employee Performance
  • Human Resource and Talent Management
  • Economic Development and Digital Transformation
  • Software Engineering Research
  • Advanced Neural Network Applications
  • Economic and Technological Developments in Russia
  • Explainable Artificial Intelligence (XAI)
  • Cutaneous Melanoma Detection and Management
  • Organizational Leadership and Management Strategies
  • Advanced Image Processing Techniques

Indian Institute of Technology Jodhpur
2023-2024

Veer Bahadur Singh Purvanchal University
2011

Computer programming textbooks and software documentations often contain flowcharts to illustrate the flow of an algorithm or procedure. Modern OCR engines tag these as graphics ignore them in further processing. In this paper, we work towards making flowchart images machine-interpretable by converting executable Python codes. To end, inspired recent success natural language code generation literature, present a novel transformer-based framework, namely FloCo-T5. Our model is well-suited for...

10.48550/arxiv.2501.17441 preprint EN arXiv (Cornell University) 2025-01-29

In this work, we study one-shot video object localization problem that aims to localize instances of unseen objects in the target using a single query image object. Toward addressing challenging problem, extend popular and successful detection method, namely DETR (Detection Transformer), introduce novel approach –query-guided transformer for videos (QDETRv). A distinctive feature QDETRv is its capacity exploit information from spatio-temporal context video, which significantly aids precisely...

10.1609/aaai.v38i3.28063 article EN Proceedings of the AAAI Conference on Artificial Intelligence 2024-03-24

Interpreting visual relationships is a core aspect of comprehensive video understanding. Given query relationship as <subject, predicate, object> and test video, our objective to localize the subject object that are connected via predicate. modern visio-lingual understanding capabilities, solving this problem achievable, provided there large-scale annotated training examples available. However, annotating for every combination subject, object, predicate cumbersome, expensive, possibly...

10.1109/cvpr52729.2023.00227 article EN 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023-06-01

The objective of this study is to make an attempt find out gaps, if any, between the "Employee Readiness implement HR practices" employees Public Sector and Private Sector. Data was collected from sector Sectors. Questionnaire method used collect responses respondents. Employee Index calculated. Statistical technique t-test ANOVA were analyze data. Results showed that there a significant difference Further all three organizations i.e. large, medium small scale differ significantly on...

10.18090/samriddhi.v2i1.1592 article EN SAMRIDDHI A Journal of Physical Sciences Engineering and Technology 2011-06-25
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