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ORCID51st AIPR 2022: Washington, DC, USA
- 51st IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2022, Washington, DC, USA, October 11-13, 2022. IEEE 2022, ISBN 978-1-6654-7729-1
- Anna Snarski, Walker L. Dimon, Keith Manville, Michael Krumdick:
Watermarking for Data Provenance in Object Detection. 1-7 - Nicholas S. Noboa, John W. Von Holle, Paul A. Brown, John M. Irvine:
Utilization of Artificial Intelligence in Automated Image Analysis. 1-6 - Abdulkadir Korkmaz, Ahmad Alhonainy, Praveen Rao:
An Evaluation of Federated Learning Techniques for Secure and Privacy-Preserving Machine Learning on Medical Datasets. 1-7 - Adam Van Etten:
The Weaknesses of Adversarial Camouflage in Overhead Imagery. 1-7 - Ilyas Bankole-Hameed, Arav Parikh, Josh Harguess:
Exploring the Effect of Adversarial Attacks on Deep Learning Architectures for X-Ray Data. 1-9 - Timothy Krock, Jaired Collins, Joshua Fraser
, Hadi Ali Akbarpour, Kannappan Palaniappan:
A Down-to-Earth Approach for Camera to World Map Georeferencing Using SfM. 1-7 - Xiwen Chen, Bryce Hopkins, Hao Wang, Leo O'Neill, Fatemeh Afghah, Abolfazl Razi, Peter Z. Fulé, Janice Coen, Eric Rowell, Adam C. Watts:
Wildland Fire Detection and Monitoring using a Drone-collected RGB/IR Image Dataset. 1-4 - Mohammad Zarei, Chris M. Ward, Josh Harguess, Marshal Aiken:
Adversarial Barrel! An Evaluation of 3D Physical Adversarial Attacks. 1-6 - Anne Watson, Ekincan Ufuktepe, Kannappan Palaniappan:
Detecting Software Code Vulnerabilities Using 2D Convolutional Neural Networks with Program Slicing Feature Maps. 1-9 - Yao Du, Carlos M. Mateo, Omar Tahri:
Robot Rotation Estimation Using Spherical Moments in Neural Networks. 1-7 - Maria Balega, Waleed Farag, Soundararajan Ezekiel, Xin-Wen Wu, Alicia Deak, Zaryn Good:
IoT Anomaly Detection Using a Multitude of Machine Learning Algorithms. 1-7 - Mei Qiu, Lauren A. Christopher, Stanley Y. P. Chien, Yaobin Chen:
Attention Mechanism Improves YOLOv5x for Detecting Vehicles on Surveillance Videos. 1-8 - William Boler, Ashley S. Dale, Lauren A. Christopher:
Trusted Data Anomaly Detection (TaDA) in Ground Truth Image Data. 1-6 - Dhanuj Mount Gandikota, Taissa Gladkova, Kha-Ai Tran, Sanika Bapat, Jennifer A. Richkus, Jeffrey Arnold:
AI Augmentation to Remote Sensing Imagery in Forestry Conservation & Restoration for Increased Responsive Capabilities. 1-16 - Joel Bornemann, Matthew D. Reisman, Steven Esposito, Timothy Berrill, Joshua Wall, Todd Conway, Jesse Boone, Ryan Soldin:
Latent-Space Analysis for Improved Overhead Imagery Explainability. 1-8 - Maria J. P. Peixoto, Akramul Azim, Jim Sheehan, Dan Timothy:
An Intelligent Traffic Monitoring Embedded System using Video Data Mining. 1-6 - Melanie Jutras, Ethan Liang, Sara Leary, Chris M. Ward, Keith Manville:
Detecting Physical Adversarial Patch Attacks with Object Detectors. 1-7 - Destie Provenzano, Yuan James Rao, Murray H. Loew, Shawn Haji-Momenian:
Exploring the Explainability of Machine Learning Algorithms for Prostate Cancer. 1-5 - Elan Sharghi, Jacob Rodriguez, Justin Mauger, Martin Jaszewski, Shibin Parameswaran:
Maritime Object Detection with Event-Based Cameras. 1-7 - Koundinya Nouduri, Jason James, Joshua Fraser, Hadi Ali Akbarpour, Kannappan Palaniappan:
A comparison of features Synthetic WAMI and GES of the same location. 1-8 - Philip Bailey, Andrew Clevenger, Hakki Erhan Sevil:
Traversability Assessment and Reachability Analysis for Unmanned Ground Vehicles through Image Segmentation. 1-5 - Steven A. Israel, John M. Irvine, Ieuan M. Israel:
Toward CNN Architectures for Image Detection. 1-6 - Andrew Kalukin:
Codomain Transformation to Represent Abstract Information for Machine Learning in Visual Scenes. 1-5 - Shengfang Ma, Yuting Zhou, K. Colton Flynn, Sathyanarayanan N. Aakur:
Peanut Seed Germination Detection from Aerial Images. 1-6 - Shuyue Guan, Ravi K. Samala, Weijie Chen:
Informing selection of performance metrics for medical image segmentation evaluation using configurable synthetic errors. 1-8 - Zeyu Zhang, Callista Baker, Noor Azam-Naseeruddin, Jingzhou Shen, Robert Pless:
What Does Learning About Time Tell About Outdoor Scenes? 1-6 - Teena Sharma, Bhanu Teja Nalla, Nishchal K. Verma, Shantaram Vasikarla:
FR-HDNet: Faster RCNN based Haze Detection Network for Image Dehazing. 1-8 - Rachida Kone, Otily Toutsop, Ketchiozo Thierry Wandji, Kevin T. Kornegay, Joy Falaye:
Adversarial Machine Learning Attacks in Internet of Things Systems. 1-7 - Rafael De Sa Lowande, Arash Golibagh Mahyari, Hakki Erhan Sevil:
Post-Disaster Damage Detection using Aerial Footage: Visual Question Answering (VQA) Case Study. 1-4 - Jeremy Straub:
Increasing Trust in Artificial Intelligence with a Defensible AI Technique. 1-7 - Mike Busch, Andrew Funk, Matt McIlvride, Trevor Thomas, Brian Fuller, Dan Blair, John Chapman:
A Novel Programmatic Hybrid 2D / 3D Image Segmentation and Labeling Methodology. 1-8 - Dagen Braun, Matthew D. Reisman, Larry Dewell, Andrzej Banburski-Fahey, Arturo Deza, Tomaso A. Poggio:
Achieving Adversarial Robustness in Deep Learning-Based Overhead Imaging. 1-7 - Josh Harguess, Chris M. Ward:
Is the Next Winter Coming for AI? Elements of Making Secure and Robust AI. 1-7 - Ashley S. Dale, Mei Qiu, Lauren A. Christopher, Wendy Krogg, Albert William:
CNN-based network has Network Anisotropy -work harder to learn rotated feature than non-rotated feature. 1-5 - Sofia Hirschmann, James Tanis, Nazario Irizarry, B. Ann Martin, Michelle Brennan, John M. Irvine:
The Relationship Between Tracking Performance and Video Quality. 1-6 - Mohammad R. Alam, Chris M. Ward:
Adversarial Examples in Self-Driving: A Review of Available Datasets and Attacks. 1-6 - Nguyen P. Nguyen, Stephanie Lopez, Catherine L. Smith, Teresa E. Lever, Nicole L. Nichols, Filiz Bunyak:
Axon and Myelin Sheath Segmentation in Electron Microscopy Images using Meta Learning. 1-6 - Yaesop Lee, Hyungtae Lee, Eungjoo Lee, Heesung Kwon, Shuvra S. Bhattacharyya:
Exploiting Simplified Depth Estimation for Stereo-based 2D Object Detection. 1-6 - Michael J. Reale, Preston Nichols, Ethan Schneider, Morgan Bishop, Maria Cornacchia:
Generative Adversarial Networks for Vehicle Transformation in Overhead and Satellite Imagery. 1-13 - Darrell L. Young, Mark Bigham, Mark Bradbury, Eric Larson, Mitchell A. Thornton:
SMU-DDI Cyber Autonomy Range. 1-5 - Zakariya A. Oraibi, Safaa Albasri:
Predicting COVID-19 from Chest X-ray Images using a New Deep Learning Architecture. 1-6
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