collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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.…

eess.IV2026

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…

eess.IV2026

A UAV-Based VNIR Hyperspectral Benchmark Dataset for Landmine and UXO Detection

Sagar Lekhak, Emmett J. Ientilucci, Jasper Baur +1

This paper introduces a novel benchmark dataset of Visible and Near-Infrared (VNIR) hyperspectral imagery acquired via an unmanned aerial vehicle (UAV) platform for landmine and un…

cs.CV2025

Uncertainty Quantification In Surface Landmines and UXO Classification Using MC Dropout

Sagar Lekhak, Emmett J. Ientilucci, Dimah Dera +1

Detecting surface landmines and unexploded ordnances (UXOs) using deep learning has shown promise in humanitarian demining. However, deterministic neural networks can be vulnerable…