6 citations · 22 across the 35 of their papers we have counts for
4 papers · 1 filter
Brain-inspired spike-timing plasticity for reliable label-efficient event-camera vision
Mohamad Yazan Sadoun, Sarah Sharif, Yaser Mike Banad
Deploying event-camera object detectors is constrained by per-frame labeling requirements and GPU compute demands. This work introduces three local spike-timing-dependent plasticit…
IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0
Mohsen Asghari Ilani, Yaser Mike Banad
This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional neural networks (CNNs). By int…
SparseVoxelDet: Fully Sparse Voxel Networks for Efficient Event-Based Drone Detection
Mohamad Yazan Sadoun, Sarah Sharif, Yaser Mike Banad
Event cameras excel at detecting small, fast drones, but today's detectors give away their key advantage: they convert the sparse event stream into dense grids and pay dense-proces…
TransMatch: A Transfer-Learning Framework for Defect Detection in Laser Powder Bed Fusion Additive Manufacturing
Mohsen Asghari Ilani, Yaser Mike Banad
Surface defects in Laser Powder Bed Fusion (LPBF) pose significant risks to the structural integrity of additively manufactured components. This paper introduces TransMatch, a nove…