2 citations · 3 across the 6 of their papers we have counts for
6 papers
SULAND v2: A Refined RGB Dataset and Deep Learning Object Detection Benchmark for UAV/UGV-Based SUrface LANDmine Detection Under Domain Shift
Sagar Lekhak, Prasanna Reddy Pulakurthi, Lalit Joshi +2
RGB imagery offers a practical, low-cost option for Unmanned Aerial/Ground Vehicle (UAV/UGV) survey support in surface-landmine detection, but object detectors remain underexplored…
Human-in-the-Loop Signature Bootstrapping for UAV Hyperspectral PFM-1 Mine Detection
Sagar Lekhak, Prasanna Reddy Pulakurthi, Emmett J. Ientilucci
Hyperspectral imaging (HSI) is useful for material discrimination, but operational mine screening also depends on how many false alarms must be inspected before targets are found.…
Benchmarking Deep Learning and Statistical Target Detection Methods for PFM-1 Landmine Detection in UAV Hyperspectral Imagery
Sagar Lekhak, Prasanna Reddy Pulakurthi, Ramesh Bhatta +1
In recent years, unmanned aerial vehicles (UAVs) equipped with imaging sensors and automated processing algorithms have emerged as a promising tool to accelerate large-area surveys…
X-CoT: Explainable Text-to-Video Retrieval via LLM-based Chain-of-Thought Reasoning
Prasanna Reddy Pulakurthi, Jiamian Wang, Majid Rabbani +3
Prevalent text-to-video retrieval systems mainly adopt embedding models for feature extraction and compute cosine similarities for ranking. However, this design presents two limita…
Shuffle PatchMix Augmentation with Confidence-Margin Weighted Pseudo-Labels for Enhanced Source-Free Domain Adaptation
Prasanna Reddy Pulakurthi, Majid Rabbani, Jamison Heard +3
This work investigates Source-Free Domain Adaptation (SFDA), where a model adapts to a target domain without access to source data. A new augmentation technique, Shuffle PatchMix (…
Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data
Prasanna Reddy Pulakurthi, Majid Rabbani, Celso M. de Melo +2
This paper introduces a novel dual-region augmentation approach designed to reduce reliance on large-scale labeled datasets while improving model robustness and adaptability across…