23 citations · 23 across the 8 of their papers we have counts for
7 papers · 1 filter
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.…
Improved Knowledge Distillation for Land-Use Image Classification
Arundhuti Sur, Abhiroop Chatterjee, Susmita Ghosh +1
In the present article, an improved Knowledge Distillation (KD) framework has been proposed for efficient compression of deep convolutional neural networks for land-use image class…
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…
Adaptive Contextual Embedding for Robust Far-View Borehole Detection
Xuesong Liu, Tianyu Hao, Emmett J. Ientilucci
In controlled blasting operations, accurately detecting densely distributed tiny boreholes from far-view imagery is critical for operational safety and efficiency. However, existin…
SmokeNet: Efficient Smoke Segmentation Leveraging Multiscale Convolutions and Multiview Attention Mechanisms
Xuesong Liu, Emmett J. Ientilucci
Efficient segmentation of smoke plumes is crucial for environmental monitoring and industrial safety, enabling the detection and mitigation of harmful emissions from activities lik…