Trajectory Learning for Robot Programming by Demonstration Using Hidden Markov Model and Dynamic Time Warping. - Aleksandar Vakanski; Iraj Mantegh; Andrew Irish; Farrokh Janabi-Sharifi (IEEE Trans. Syst. Man Cybern. Part B, 2012)

A secure architecture for IoT with supply chain risk management. - Robert E. Hiromoto; Michael A. Haney; Aleksandar Vakanski (IDAACS, 2017)

An image-based trajectory planning approach for robust robot programming by demonstration. - Aleksandar Vakanski; Farrokh Janabi-Sharifi; Iraj Mantegh (Robotics Auton. Syst., 2017)

Generative adversarial networks for generation and classification of physical rehabilitation movement episodes. - Longze Li; Aleksandar Vakanski (CoRR, 2018)

A Data Set of Human Body Movements for Physical Rehabilitation Exercises. - Aleksandar Vakanski; Hyung-pil Jun; David Paul; Russell Baker (Data, 2018)

A Deep Learning Framework for Assessing Physical Rehabilitation Exercises. - Yalin Liao; Aleksandar Vakanski; Min Xian (CoRR, 2019)

Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images. - Aleksandar Vakanski; Min Xian; Phoebe Freer (CoRR, 2019)

Stan: Small Tumor-Aware Network for Breast Ultrasound Image Segmentation. - Bryar Shareef; Min Xian; Aleksandar Vakanski (ISBI, 2020)

Bending Loss Regularized Network for Nuclei Segmentation in Histopathology Images. - Haotian Wang 005; Min Xian; Aleksandar Vakanski (ISBI, 2020)

A review of computational approaches for evaluation of rehabilitation exercises. - Yalin Liao; Aleksandar Vakanski; Min Xian; David Paul; Russell Baker (Comput. Biol. Medicine, 2020)

ESTAN: Enhanced Small Tumor-Aware Network for Breast Ultrasound Image Segmentation. - Bryar Shareef; Aleksandar Vakanski; Min Xian; Phoebe E. Freer (CoRR, 2020)

Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image Analysis. - Aleksandar Vakanski; Min Xian (MLSP, 2021)

Bi-Rads-Net: An Explainable Multitask Learning Approach for Cancer Diagnosis in Breast Ultrasound Images. - Boyu Zhang 004; Aleksandar Vakanski; Min Xian (MLSP, 2021)

Potato Crop Stress Identification in Aerial Images using Deep Learning-based Object Detection. - Sujata Butte; Aleksandar Vakanski; Kasia Duellman; Haotian Wang 005; Amin Mirkouei (CoRR, 2021)

Sharp-GAN: Sharpness Loss Regularized GAN for Histopathology Image Synthesis. - Sujata Butte; Haotian Wang 005; Min Xian; Aleksandar Vakanski (ISBI, 2022)

EMT-NET: Efficient Multitask Network for Computer-Aided Diagnosis of Breast Cancer. - Jiaqiao Shi; Aleksandar Vakanski; Min Xian; Jianrui Ding; Chunping Ning (ISBI, 2022)

MIRST-DM: Multi-instance RST with Drop-Max Layer for Robust Classification of Breast Cancer. - Shoukun Sun; Min Xian; Aleksandar Vakanski; Hossny Ghanem (MICCAI (4), 2022)

TA-Net: Topology-Aware Network for Gland Segmentation. - Haotian Wang 005; Min Xian; Aleksandar Vakanski (WACV, 2022)

Enhanced Sharp-Gan for Histopathology Image Synthesis. - Sujata Butte; Haotian Wang 005; Aleksandar Vakanski; Min Xian (ISBI, 2023)

SIAN: Style-Guided Instance-Adaptive Normalization for Multi-Organ Histopathology Image Synthesis. - Haotian Wang 005; Min Xian; Aleksandar Vakanski; Bryar Shareef (ISBI, 2023)

Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network. - Bryar Shareef; Min Xian; Aleksandar Vakanski; Haotian Wang 005 (MICCAI (4), 2023)

Post-Hoc Explainability of BI-RADS Descriptors in a Multi-Task Framework for Breast Cancer Detection and Segmentation. - Mohammad Karimzadeh; Aleksandar Vakanski; Min Xian; Boyu Zhang 004 (MLSP, 2023)

BI-RADS-NET-V2: A Composite Multi-Task Neural Network for Computer-Aided Diagnosis of Breast Cancer in Ultrasound Images With Semantic and Quantitative Explanations. - Boyu Zhang 004; Aleksandar Vakanski; Min Xian (IEEE Access, 2023)

Machine Learning Methods for Cancer Classification Using Gene Expression Data: A Review. - Fadi Alharbi; Aleksandar Vakanski (CoRR, 2023)

Review of Machine Learning Methods for Additive Manufacturing of Functionally Graded Materials. - Mohammad Karimzadeh; Aleksandar Vakanski; Fei Xu; Xinchang Zhang (CoRR, 2023)

Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks. - Longze Li; Jiang Chang; Aleksandar Vakanski; Min Xian (CoRR, 2023)

A2DMN: Anatomy-Aware Dilated Multiscale Network for Breast Ultrasound Semantic Segmentation. - Kyle Lucke; Aleksandar Vakanski; Min Xian (ISBI, 2024)

Do Sharpness-based Optimizers Improve Generalization in Medical Image Analysis? - Mohamed Hassan; Aleksandar Vakanski; Min Xian (CoRR, 2024)

LASSO-MOGAT: A Multi-Omics Graph Attention Framework for Cancer Classification. - Fadi Alharbi; Aleksandar Vakanski; Murtada Khalafallah Elbashir; Mohanad Mohammed (CoRR, 2024)

Comparative Analysis of Multi-Omics Integration Using Advanced Graph Neural Networks for Cancer Classification. - Fadi Alharbi; Aleksandar Vakanski; Boyu Zhang 004; Murtada K. Elbashir; Mohanad Mohammed (CoRR, 2024)

Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Images. - Haotian Wang 005; Aleksandar Vakanski; Changfa Shi; Min Xian (Inf., 2024)

Semantic-Aware Adaptive Binary Search for Hard-Label Black-Box Attack. - Yiqing Ma; Kyle Lucke; Min Xian; Aleksandar Vakanski (Comput., 2024)

Comparative Analysis of Multi-Omics Integration Using Graph Neural Networks for Cancer Classification. - Fadi Alharbi; Aleksandar Vakanski; Boyu Zhang 004; Murtada K. Elbashir; Mohanad Mohammed (IEEE Access, 2025)

Automated Skin Cancer Report Generation via a Knowledge-Distilled Vision-Language Model. - Lawhori Chakrabarti; Boyu Zhang 004; Hengyi Tian; Aleksandar Vakanski; Min Xian (IEEE Access, 2025)

Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? - Mohamed Hassan; Aleksandar Vakanski; Boyu Zhang 004; Min Xian (IEEE Access, 2025)

Soft-Label Supervised Meta-Model with Adversarial Samples for Uncertainty Quantification. - Kyle Lucke; Aleksandar Vakanski; Min Xian (Comput., 2025)

GCSAM: Gradient Centralized Sharpness Aware Minimization. - Mohamed Hassan; Aleksandar Vakanski; Boyu Zhang 004; Min Xian (CoRR, 2025)

Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning. - Jiang Chang; Deekshith Basvoju; Aleksandar Vakanski; Indrajit Charit; Min Xian (CoRR, 2025)

Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification, An Interpretable Multi-Omics Approach. - Fadi Alharbi; Nishant Budhiraja; Aleksandar Vakanski; Boyu Zhang 004; Murtada K. Elbashir; Mohanad Mohammed (CoRR, 2025)

Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems. - Matthew Sgambati; Aleksandar Vakanski; Matthew Anderson (CoRR, 2025)