publications

2025

1. SPIE

   

   Texture analysis of lung cell surface morphology after nanoparticle exposure

   Akshatha Mohan, Trevor Jefferis, Christie M. Sayes, and 1 more author

   In Medical Imaging 2025: Digital and Computational Pathology, 2025

   Abs Bib

   We quantify morphological imaging metrics such as lacunarity and fractal dimension of lung cell surfaces from SEM images, relating them to dendritic cell sensitization following nanoparticle exposure, and introduce a Quantization and Counting Operator (QCO) for statistical texture analysis.

   @inproceedings{mohan2025texture,
     title = {Texture analysis of lung cell surface morphology after nanoparticle exposure},
     author = {Mohan, Akshatha and Jefferis, Trevor and Sayes, Christie M. and Peeples, Joshua},
     booktitle = {Medical Imaging 2025: Digital and Computational Pathology},
     volume = {13413},
     pages = {221--230},
     year = {2025},
     organization = {SPIE},
   }

2024

1. CVPRW

   

   Lacunarity Pooling Layers for Plant Image Classification using Texture Analysis

   Akshatha Mohan and Joshua Peeples

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Jun 2024

   Abs Bib HTML PDF

   We introduce lacunarity pooling layers that leverage texture information to improve image classification, achieving up to 98.07% accuracy on PlantVillage and 95.00% on LeavesTex1200 with minimal additional parameters.

   @inproceedings{mohan2024lacunarity,
     title = {Lacunarity Pooling Layers for Plant Image Classification using Texture Analysis},
     author = {Mohan, Akshatha and Peeples, Joshua},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
     pages = {5384--5392},
     year = {2024},
     month = jun,
   }

2. arXiv

   

   Spatial Transformer Network YOLO Model for Agricultural Object Detection

   Yash Zambre, Ekdev Rajkitkul, Akshatha Mohan, and 1 more author

   In , 2024

   arXiv Bib HTML

   @inproceedings{zambre2024spatial,
     title = {Spatial Transformer Network YOLO Model for Agricultural Object Detection},
     author = {Zambre, Yash and Rajkitkul, Ekdev and Mohan, Akshatha and Peeples, Joshua},
     year = {2024},
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
   }

2023

1. IGARSS

   

   Quantitative Analysis of Primary Attribution Explainable Artificial Intelligence Methods for Remote Sensing Image Classification

   Akshatha Mohan and Joshua Peeples

   In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023

   Abs DOI arXiv Bib HTML

   We evaluate primary-attribution XAI methods (LIME, HiResCAM, GradSHAP, Saliency, Occlusion) across multispectral and SAR imagery using a six-category metric framework spanning faithfulness, robustness, and localization.

   @inproceedings{mohan2023quantitative,
     title = {Quantitative Analysis of Primary Attribution Explainable Artificial Intelligence Methods for Remote Sensing Image Classification},
     author = {Mohan, Akshatha and Peeples, Joshua},
     booktitle = {IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium},
     pages = {950--953},
     year = {2023},
     doi = {10.1109/IGARSS52108.2023.10281981},
   }

2022

1. AISP

   

   Generation of Netlist from a Hand Drawn Circuit through Image Processing and Machine Learning

   Akshatha Mohan, Apoorva Mohan, B. Indushree, and 2 more authors

   In 2022 IEEE 2nd International Conference on Artificial Intelligence and Signal Processing (AISP), 2022

   DOI Bib

   @inproceedings{mohan2022generation,
     title = {Generation of Netlist from a Hand Drawn Circuit through Image Processing and Machine Learning},
     author = {Mohan, Akshatha and Mohan, Apoorva and Indushree, B. and Malavikaa, M. and Narendra, C. P.},
     booktitle = {2022 IEEE 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)},
     pages = {1--4},
     year = {2022},
     doi = {10.1109/AISP53593.2022.9760577},
   }