Predicting mechanical properties of Carbon Nanotube (CNT) images Using Multi-Layer Synthetic Finite Element Model Simulations

no code implementations • 16 Jul 2023 • Kaveh Safavigerdini, Koundinya Nouduri, Ramakrishna Surya, Andrew Reinhard, Zach Quinlan, Filiz Bunyak, Matthew R. Maschmann, Kannappan Palaniappan

We present a pipeline for predicting mechanical properties of vertically-oriented carbon nanotube (CNT) forest images using a deep learning model for artificial intelligence (AI)-based materials discovery.

Data Augmentation

Real-Time Helmet Violation Detection in AI City Challenge 2023 with Genetic Algorithm-Enhanced YOLOv5

no code implementations • 13 Apr 2023 • Elham Soltanikazemi, Ashwin Dhakal, Bijaya Kumar Hatuwal, Imad Eddine Toubal, Armstrong Aboah, Kannappan Palaniappan

The results demonstrate impressive precision, recall, and mAP scores of 0. 848, 0. 599, and 0. 641, respectively for the training data.

Data Augmentation object-detection +1

Multi-Cue Vehicle Detection for Semantic Video Compression In Georegistered Aerial Videos

no code implementations • 2 Jul 2019 • Noor Al-Shakarji, Filiz Bunyak, Hadi Aliakbarpour, Guna Seetharaman, Kannappan Palaniappan

Detection of moving objects such as vehicles in videos acquired from an airborne camera is very useful for video analytics applications.

Cloud Computing Image Compression +3

Multi-Scale Spatially Weighted Local Histograms in O(1)

no code implementations • 9 May 2017 • Mahdieh Poostchi, Ali Shafiekhani, Kannappan Palaniappan, Guna Seetharaman

Weighting pixel contribution considering its location is a key feature in many fundamental image processing tasks including filtering, object modeling and distance matching.