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ORCID50th AIPR 2021: Washington, DC, USA
- 50th IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2021, Washington, DC, USA, October 12-14, 2021. IEEE 2021, ISBN 978-1-6654-2471-4
- Zhaohui Liang
, Jimmy Xiangji Huang:
Adaptive Cycle-consistent Adversarial Network for Malaria Blood Cell Image Synthetization. 1-7 - Bhagyasree Kanuparthi, Anish C. Turlapaty, Balakrishna Gokaraju:
An Ensemble Approach for Classification of Reach and Grasp Movements based on EEG Signals. 1-6 - Shuyue Guan, Murray H. Loew:
A Sneak Attack on Segmentation of Medical Images Using Deep Neural Network Classifiers. 1-8 - Stefan Jaeger:
The Golden Ratio in Machine Learning. 1-7 - Mariia Sidulova, Nina Nehme, Chung Hyuk Park:
Towards Explainable Image Analysis for Alzheimer's Disease and Mild Cognitive Impairment Diagnosis. 1-6 - Jonathan Schierl, Vijayan K. Asari, Nina M. Singer, Theus H. Aspiras, Andrew Stokes, Brett Keaffaber, Andre van Rynbach, Kevin Decker, David Rabb:
A Feature Level Multi-Sensor Information Fusion Strategy for Land Region Classification. 1-7 - Qinwen Huang, Ye Zhou, Alberto Bartesaghi:
Joint Model for Image Denoising and Detection of Proteins Imaged by Cryo-EM. 1-8 - Michael Threet, Colin Busho, Josh Harguess, Melanie Jutras, Nicole Lape, Sara Leary, Keith Manville, Mike Tan, Chris M. Ward:
Physical Adversarial Attacks in Simulated Environments. 1-5 - Emily Holt, Anto Malkastian, Savanna Smith, Chris M. Ward, Josh Harguess:
Baseline Evaluation Methodology for Adversarial Patterns on Object Detection Models. 1-6 - Jonathan Bouvette, Qinwen Huang, Alberto Bartesaghi, Mario J. Borgnia:
Smartscope: AI-driven grid navigation for high-throughput cryo-EM. 1-6 - Deniz Kavzak Ufuktepe, Feng Yang, Yasmin M. Kassim, Hang Yu, Richard James Maude, Kannappan Palaniappan, Stefan Jaeger:
Deep Learning-Based Cell Detection and Extraction in Thin Blood Smears for Malaria Diagnosis. 1-6 - Ieuan M. Israel, Steven A. Israel, John M. Irvine:
Factors Influencing CNN Performance. 1-4 - Soma Biswas, Debmalya Biswas:
Deep Learning based Asbestos Fiber Detection. 1-5 - Sai Krishna Charitha Tallapragada, Anish C. Turlapaty, Balakrishna Gokaraju, Enoch Sarku:
Optimal Features for Cross Subject Classification of Imagined Left and Right Fist Movements using EEG Signals. 1-5 - Keli Cheng, Trevor M. Bajkowski, Grant J. Scott:
Evaluation of Sentinel-2 Data for Automatic Maasai Boma Mapping. 1-5 - Aneesh Bhattacharya, Vijayan K. Asari:
Wearable Walking Aid System to Assist Visually Impaired Persons to Navigate Sidewalks. 1-7 - Ashish Pandey, Ramakrishna Surya, Matthew R. Maschmann, Prasad Calyam:
Reinforcement Learning based Carbon Nanotube Growth Automation. 1-10 - Apurva Pandya, Catherine Samuel, Nisargkumar Patel, Vaibhavkumar Patel, Thangarajah Akilan:
Multi-channel MRI Embedding: An Effective Strategy for Enhancing Brain Tumor Segmentation. 1-8 - Roland Oruche, Eric D. Milman, Xiyao Cheng, Megha Joish, Chaitra T. Kulkarni, Agrim Sharma, Kerk F. Kee, Hariharan Regunath, Prasad Calyam:
Measurement of Utility in User Access of COVID-19 Literature via AI-powered Chatbot. 1-13 - Jing Wang, Yousuf El-Jayyousi, Ilker Ozden:
Seizure detection in EEG using dynamic system analysis. 1-5 - Kenyon Shutt, Wan Fatimah Wan Nawawi, Gillian Schulte, Juan Martinez-Sainz, Ekincan Ufuktepe, Kannappan Palaniappan:
Auto-SDist: An Automatic COVID-19 Social Distancing and Room Management System Architecture for Indoors. 1-6 - Chenxi Zhao, Ye Duan, Deshan Yang:
A Deep Learning Approach for Contour Interpolation. 1-5 - Payal Mohadikar, Ye Duan, Steven Carr:
Brain Intracranial Hemorrhage Segmentation using Unsupervised Learning on Volume CT Images. 1-5 - Nguyen P. Nguyen, Tommi A. White, Filiz Bunyak:
Mitochondria Instance Segmentation in Electron Microscopy Image Volumes using 3D Deep Learning Networks. 1-6 - Shiri Bendelac, Keith Manville, Josh Harguess, Mikel Rodriguez:
A Dynamic Thermal IR Display for Physical Adversarial Attacks. 1-7 - Mitch Kinney, Mike Hadjimichael, Matt Cotter, Monica P. Carley-Spencer:
Using Image Processing for Architecture Extraction from Non-Standard Sources. 1-7 - Nina M. Singer, Vijayan K. Asari, Theus H. Aspiras, Jonathan Schierl, Andrew Stokes, Brett Keaffaber, Andre van Rynbach, Kevin Decker, David Rabb:
Attention Focused Generative Network for Reducing Self-Occlusions in Aerial LiDAR. 1-7 - John M. Irvine, Brigid Angelini, Michael R. Crystal:
Remote Sensing Predicts Long-term Indicators of Governance, Stability, and Well-being. 1-10 - Tan H. Nguyen, Pham Duy Hai, Cong Son Doan Huynh, Huy Tan Nguyen:
Aceso: A Medical Image Analysis Platform Using Deep Learning. 1-6 - Yang Yang Wang, Olga V. Glinskii, Filiz Bunyak, Kannappan Palaniappan:
Ensemble of Deep Learning Cascades for Segmentation of Blood Vessels in Confocal Microscopy Images. 1-7 - Feng Yang, Hang Yu, Karthik Kantipudi, Alex Rosenthal, Darrell E. Hurt, Ziv Yaniv, Stefan Jaeger:
Automated Drug-Resistant TB Screening: Importance of Demographic Features and Radiological Findings in Chest X-Ray. 1-4 - Hrishikesh Tiwary, Arnav Bhavsar:
Time-Frequency Representations for EEG Artifact Classification with CNNs. 1-8 - Blake Bleem, Jordan Renaud, Thi T. Tuyen Nguyen, Srija Bandyopadhayay, Asit Bandyopadhayay, Reshmi Mitra:
Anonymized Blockchain-Based Infection Tracking for Disease Control. 1-4 - Trevor M. Bajkowski, J. Alex Hurt, Jeffrey Dale, David Huangal, James M. Keller, Grant J. Scott, Stanton R. Price:
Evaluating Visuospatial Features for Tracking Hazards in Overhead UAS Imagery. 1-6 - R. N. Beena Priya, Madasu Hanmandlu, Shantaram Vasikarla:
Emotion Recognition Using Deep Learning. 1-5 - Mostofa Rafid Uddin, Ajmain Yasar Ahmed, Kafi Khan, Md Shahrar Fatemi, Xiangrui Zeng, Min Xu:
Practical Analysis of Macromolecule Identity from Cryo-electron Tomography Images using Deep Learning. 1-9 - Destie Provenzano, Yuan James Rao, Sharad Goyal, Shawn Haji-Momenian, John Lichtenberger, Murray H. Loew:
Radiologist vs Machine Learning: A Comparison of Performance in Cancer Imaging. 1-10 - Gani Rahmon, Imad Eddine Toubal, Kannappan Palaniappan:
Extending U-Net Network for Improved Nuclei Instance Segmentation Accuracy in Histopathology Images. 1-7 - Yang Yang Wang, Ke Gao, Ali S. Hamad, Brianna McCarthy, Ashley M. Kloepper, Teresa E. Lever, Filiz Bunyak:
Multi-Modal and Multi-Scale Oral Diadochokinesis Analysis using Deep Learning. 1-6 - Elan Sharghi, Peter Thung, Jane Berk, Arne Odland, Shibin Parameswaran:
Effects of data preparation, training and testing choices on classifier performance: Case study in ship classification. 1-6 - Stephanie Aelmore, Richard C. Ordonez, Shibin Parameswaran, Justin Mauger:
Real-Time Event-Based Tracking and Detection for Maritime Environments. 1-6
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