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Shubham

Publications and source records attributed to Shubham.

7 recordsLinked to original sources
arXiv2026

TreeDGS: Aerial Gaussian Splatting for Distant DBH Measurement

Aerial remote sensing efficiently surveys large areas, but accurate direct object-level measurement remains difficult in complex natural scenes. Advancements in 3D computer vision, particularly radiance field representations such as NeRF and 3D Gaussian splatting, can improve reconstruction fidelity from posed imagery. Nevertheless, direct aerial measurement of important attributes like tree diameter at breast height (DBH) remains challenging. Trunks in aerial forest scans are distant and sparsely observed in image views; at typical operating altitudes, stems may span only a few pixels. With these constraints, conventional reconstruction methods have inaccurate breast-height trunk geometry. TreeDGS is an aerial image reconstruction method that uses 3D Gaussian splatting as a continuous scene representation for trunk measurement. After SfM--MVS initialization and Gaussian optimization, we extract a dense point set from the Gaussian field using RaDe-GS's depth-aware cumulative-opacity integration and associate each sample with a multi-view opacity reliability score. Then, we isolate trunk points and estimate DBH using opacity-weighted solid-circle fitting. Evaluated on 10 plots with field-measured DBH, TreeDGS reaches 4.79 cm RMSE (about 2.6 pixels at this GSD) and outperforms a LiDAR baseline (7.66 cm RMSE). This shows that TreeDGS can enable accurate, low-cost aerial DBH measurement .

cs.CV↗
arXiv2024

On the Distribution of Points of Valuation 1 for a Polynomial in Two Variables

We investigate the variation in the total number of points in a random $p\times p$ square in $\mathbb{Z}^2$ where the $p$-adic valuation of a given polynomial in two variables is precisely $1$. We establish that this quantity follows a Poisson distribution as $p\rightarrow\infty$ under a certain conjecture. We also relate this conjecture to certain uniform distribution properties of a vector valued sequence.

math.NT↗
arXiv2024

Leveraging Hardware Performance Counters for Predicting Workload Interference in Vector Supercomputers

In the rapidly evolving domain of high-performance computing (HPC), heterogeneous architectures such as the SX-Aurora TSUBASA (SX-AT) system architecture, which integrate diverse processor types, present both opportunities and challenges for optimizing resource utilization. This paper investigates workload interference within an SX-AT system, with a specific focus on resource contention between Vector Hosts (VHs) and Vector Engines (VEs). Through comprehensive empirical analysis, the study identifies key factors contributing to performance degradation, such as cache and memory bandwidth contention, when jobs with varying computational demands share resources. To address these issues, we develop a predictive model that leverages hardware performance counters (HCs) and machine learning (ML) algorithms to classify and predict workload interference. Our results demonstrate that the model accurately forecasts performance degradation, offering valuable insights for future research on optimizing job scheduling and resource allocation. This approach highlights the importance of adaptive resource management strategies in maintaining system efficiency and provides a foundation for future enhancements in heterogeneous supercomputing environments.

cs.DC↗
arXiv2022

An Ensemble-based approach for assigning text to correct Harmonized system code

Industries must follow government rules and regulations around the world to classify products when assessing duties and taxes for international shipment. Harmonized System (HS) is the most standardized numerical method of classifying traded products among industry classification systems. A hierarchical ensemble model comprising of Bert-transformer, NER, distance-based approaches, and knowledge-graphs have been developed to address scalability, coverage, ability to capture nuances, automation and auditing requirements when classifying unknown text-descriptions as per HS method.

cs.AI↗
arXiv2021

Evolutionary Vaccination Games with premature vaccines to combat ongoing deadly pandemic

We consider a vaccination game that results with the introduction of premature and possibly scarce vaccines introduced in a desperate bid to combat the otherwise ravaging deadly pandemic. The response of unsure agents amid many uncertainties makes this game completely different from the previous studies. We construct a framework that combines SIS epidemic model with a variety of dynamic behavioral vaccination responses and demographic aspects. The response of each agent is influenced by the vaccination hesitancy and urgency, which arise due to their personal belief about efficacy and side-effects of the vaccine, disease characteristics, and relevant reported information (e.g., side-effects, disease statistics etc.). Based on such aspects, we identify the responses that are stable against static mutations. By analysing the attractors of the resulting ODEs, we observe interesting patterns in the limiting state of the system under evolutionary stable (ES) strategies, as a function of various defining parameters. There are responses for which the disease is eradicated completely (at limiting state), but none are stable against mutations. Also, vaccination abundance results in higher infected fractions at ES limiting state, irrespective of the disease death rate.

math.DS↗