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J. Jothi Balaji

Janarthanam Jothi Balaji

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affiliation: Medical Research Foundation, Department of Optometry, Chennai, India

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Journal Articles

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2023
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  - journals/jimaging/BhardwajBL23
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  - https://dblp.org/rec/journals/jimaging/BhardwajBL23
Rishav Bhardwaj, Janarthanam Jothi Balaji, Vasudevan Lakshminarayanan:
OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution. J. Imaging 9(11): 246 (2023)
2021
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Vasudevan Lakshminarayanan, Hoda Kheradfallah, Arya Sarkar, Janarthanam Jothi Balaji:
Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey. J. Imaging 7(9): 165 (2021)

Conference and Workshop Papers

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2022
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Hoda Kheradfallah, Janarthanam Jothi Balaji, Varadharajan Jayakumar, Mohammed Abdul Rasheed, Vasudevan Lakshminarayanan:
Annotation and segmentation of diabetic retinopathy lesions: an explainable AI application. Medical Imaging: Computer-Aided Diagnosis 2022
2020
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Amitojdeep Singh, Sourya Sengupta, J. Jothi Balaji, Mohammed Abdul Rasheed, Ibrahim Faruq, Varadharajan Jayakumar, John S. Zelek, Vasudevan Lakshminarayanan:
What is the Optimal Attribution Method for Explainable Ophthalmic Disease Classification? OMIA@MICCAI 2020: 21-31

Informal and Other Publications

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2023
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  - journals/corr/abs-2311-05146
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Rishav Bhardwaj, Janarthanam Jothi Balaji, Vasudevan Lakshminarayanan:
OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution. CoRR abs/2311.05146 (2023)
2021
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  - journals/corr/abs-2107-00115
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Vasudevan Lakshminarayanan, Hoda Kheradfallah, Arya Sarkar, J. Jothi Balaji:
Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey. CoRR abs/2107.00115 (2021)
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  - journals/corr/abs-2111-11419
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V. K. Viekash, Janarthanam Jothi Balaji, Vasudevan Lakshminarayanan:
FAZSeg: A New User-Friendly Software for Quantification of the Foveal Avascular Zone. CoRR abs/2111.11419 (2021)
2020
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  - journals/corr/abs-2009-12648
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Amitojdeep Singh, J. Jothi Balaji, Varadharajan Jayakumar, Mohammed Abdul Rasheed, Rajiv Raman, Vasudevan Lakshminarayanan:
Quantitative and Qualitative Evaluation of Explainable Deep Learning Methods for Ophthalmic Diagnosis. CoRR abs/2009.12648 (2020)

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