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Nidhi

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This is just a disambiguation page, and is not intended to be the bibliography of an actual person. The links to all actual bibliographies of persons of the same or a similar name can be found below. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.

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2020 – today

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2025
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Vineetha Joy, Aditya Anand, Nidhi, Anshuman Kumar, Amit Sethi, Hema Singh:
A Surrogate Model for the Forward Design of Multi-layered Metasurface-based Radar Absorbing Structures. CoRR abs/2505.09251 (2025)
2024
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Nidhi, Bindu Verma:
A lightweight convolutional swin transformer with cutmix augmentation and CBAM attention for compound emotion recognition. Appl. Intell. 54(17-18): 7793-7809 (2024)
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Nidhi, Jyoti Grover:
Federated learning analysis for vehicular traffic flow prediction: evaluation of learning algorithms and aggregation approaches. Clust. Comput. 27(4): 5075-5091 (2024)
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Nidhi, Gulmini Pradhan, Tarun Kapoor:
AI-Enhanced EEG-Based Personalized Mental Health Solution. ISED 2024: 1-6
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Nidhi, Avleen Sethi, Ketna Khattar, Pulkita Joshi:
Deep Learning Insights from EEG: Correlating Cognitive and Emotional Strengths. ISED 2024: 1-6
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Ramita Sahni, Ameen, Nidhi:
Entropy- Based Approach in Bug Prediction: An Overview of Theoretical and Practical Applications in Open Source Projects. WPMC 2024: 1-4
2023
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Nidhi, Bindu Verma:
From methods to datasets: a detailed study on facial emotion recognition. Appl. Intell. 53(24): 30219-30249 (2023)
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Ruby Dahiya, Nidhi, Kajal Kumari, Shruti Kumari, Nidhi Agarwal:
Usage of Web Scraping in the Pharmaceutical Sector. EAI Endorsed Trans. Pervasive Health Technol. 9 (2023)
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Bharathi Malakreddy A, Sadanand Venkataraman, Mohammed Sinan Khan, Nidhi, Srinivas Padmanabhuni, Santhi Natarajan:
Optimizing Semantic Segmentation for Enhanced Football Analytics: A Pixel-level Approach. ICMLDE 2023: 2662-2673

2010 – 2019

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2012
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Nidhi, D. K. Lobiyal:
Performance Evaluation of Realistic Vanet Using Traffic Light Scenario. CoRR abs/1203.2195 (2012)

2000 – 2009

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2006
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Nidhi, Meir Glick, John W. Davies, Jeremy L. Jenkins:
Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases. J. Chem. Inf. Model. 46(3): 1124-1133 (2006)

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