Publications
Publications
Total 100, Journal Papers: 76, Conference Papers: 24
Total 100, Journal Papers: 76, Conference Papers: 24
Research IDS:
DBLP,
International Journals
2025-26
72. Neeraj K, P. Jidesh, UWResENET: A framework for Restoration and Enhancement of Underwater Imagery using Spatial Pyramid Pooling with Low-Rank Adaptation, TVCJ (Springer), Vol. 43, 1-28, 2026 (3.7)
71. S. George, P. Jidesh et al. On the radius of convergence of an efficient High-order iterative method with applications to Image processing, JFI (Elsevier), Volume 363, Issue 14,108951,
https://doi.org/10.1016/j.jfranklin.2026.108951, 2026. (3.3)
70. Ramya S, S. George, P. Jidesh, I. Argyros, Enhancing the Practicality of Xiao and Yin’s Iterative Method, Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. (Springer), 2026, https://doi.org/10.1007/s40010-026-01066-6 (1.3)
69. P. Jidesh et al., A retinex inspired deep image prior model for despeckling and deblurring of aerial and satellite images using proximal gradient method, International Journal of Remote Sensing (Taylor and Francis) , https://doi.org/10.1080/01431161.2024.2431175, 46, pp. 1432-1466, 2025 (3.4).
68. P. Jidesh et. al., MambaDIP: Mamba-Based Deep Image Prior Framework for Despeckling and Enhancement of SAR Images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 19, pp. 21255-21271, 2026, doi: 10.1109/JSTARS.2026.3702550 (6.3).
67. Ajil K. S. George, P. Jidesh, Local and semilocal analysis of a class of fourth order methods under common set of assumptions, Applied Math. and Comp. (Elsevier), Volume 505, 15 November 2025, 129526, https://doi.org/10.1016/j.amc.2025.129526 (4)
66. A.M. Vincent, P. Jidesh "Optimizing Hyperparameters in Meta-learning for Enhanced Image Classification", IEEE Access, Vol 13, pp. 130816-130831, 2025, 10.1109/ACCESS.2025.3591142 (3.5).
65. Vincent, A.M., P. Jidesh et al. . A comprehensive analysis of hyperparameter optimization for land use, land cover classification. Multimed Tools Appl 85, 1 (2026). https://doi.org/10.1007/s11042-026-21191-z.
63. Santhosh George, Ramya Sadananda, Jidesh Padikkal, Ajil Kunnarath, Ioannis K. Argyros, New Trends on applying LRM to nonlinear ill-posed equations, Mathematics, 2024, 12, 2377. https://doi.org/10.3390/math12152377.
64. Ramya, S, S. George and P. Jidesh, On obtaining order of convergence of Jarratt-like method without using Taylor series expansion, J. Computational and Applied Mathematics (Springer), 43, 2024, https://doi.org/10.1007/s40314-024-02767-7, (2.6).
63. A. Shastry and P. Jidesh, A Self-attention driven Retinex-based Deep Image Prior model for Satellite Image Restoration, 2023, Optics and Laser Eng. (Elsevier), Vol. 173, pp. 1-18, 2023, https://doi.org/10.1016/j.optlaseng.2023.107916 (4.6).
62. Ajil K, S. George, P. Jidesh, Enhancing the applicability of a family of fifth-order iterative methods, Carpathian Journal of Mathematics, Vol 42, pp. 13-38, https://doi.org/10.37193/CJM.2026.01.02, 2025. (1.2)
61. Kunnarath, A., Gopal, M., George, S. P. Jidesh at al.. Convergence order of efficient Jarratt-like method with relaxed differentiability assumptions. Arab. J. Math. (2026). https://doi.org/10.1007/s40065-025-00604-1
2023
60. A. M. Vincent, P. Jidesh, An improved hyperparameter optimization framework for AutoML systems using evolutionary algorithms, Scientific Reports (Nature Publisher), Vol. 13, 4737 (2023). https://doi.org/10.1038/s41598-023-32027-3 (4.96).
59. A.M. Vincent, P. Jidesh, Flood susceptibility mapping using AutoML and a deep learning framework with evolutionary algorithms for hyperparameter optimization., Applied Soft Computing (Elsevier), Vol. 118, pp. 1-20, , https://doi.org/10.1016/j.asoc.2023.110846, 2023, (8.7)
58. A. Shastry, P. Jidesh, AttentionDIP: attention-based deep image prior model to restore satellite and aerial images from gamma distributed speckle interference , The Visual Computer (Springer), https://doi.org/10.1007/s00371-023-03101-8, Vol. 40, pp. 5219–5239, 2024, (3.5)
57. A. Shastry, S.George, P. Jidesh, A Weighted Nuclear Norm (WNN)-based Retinex DIP framework for restoring aerial and satellite images corrupted by gamma distributed speckle noise, Multimedia Tools and Applications (Springer), 10.1007/s11042-023-17159-y, Vol. 83, pp. 37927–37959, 2024 (3.6).
** S. George, P. Jidesh, A new parameter choice strategy and a new source condition for Tikhonov regularization method for nonlinear ill-posed equations, (Submitted), 2023 .
56. Ramya Sadananda; Santhosh George; Ajil Kunnarath ; Jidesh Padikkal; Ioannis K. Argyros, Enhancing the practicality of Newton-Cotes iterative method, J. Applied Math. and Computing (Springer), https://doi.org/10.1007/s12190-023-01886-4, 2023 (2.4)
55. Ajil Kunnarath, Santhosh George, Ramya Sadananda1, Jidesh Padikkal and Ioannis K. Argyros, On the convergence of open Newton’s method, J. Analysis (Springer), 2023, https://doi.org/10.1007/s41478-023-00572-9, Vol. 31, pp. 2473–2500, 2023 (0.8)
62. Ramya Sadananda, Santhosh George, Ioannis K. Argyros , Jidesh, Padikkal, Order of convergence and dynamics of Newton-Gauss-type methods, Fractals Fract, https://doi.org/10.3390/fractalfract7020185, 2023 (3.5)
61. Santhosh George, Ajil Kunnarath, Ramya Sadananda, Jidesh Padikkal, and Ioannis K. Argyros Order of convergence, extensions of Newton-Simpson method for solving nonlinear equations and their dynamics, Fractal Fract, 7(2), https://doi.org/10.3390/fractalfract7020163, 2023. (3.5)
60. Muhammed Saeed K, Krishnendu R., Santhosh G., Jidesh P., I. K. Argyros, Local convergence of Weerakoon-Fernando method and its extensions, Fractals Fract (MDPI), https://doi.org/10.3390/fractalfract7010098, 2022. (3.5)
59. S George, IK Argyros, A Kunnarath, P Jidesh, On the Order of Convergence and the Dynamics of Werner-King's Method, Contemporary Mathematics, 99-117, 2023.
2022
54. A. Shastry, A. Smitha, P. Jidesh, Restoration and enhancement of aerial and synthetic aperture radar images using generative deep image prior architecture, PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science (Springer), https://doi.org/10.1007/s41064-022-00226-8, Vol. 90, pp. 497–529, 2022 (4.1)
53. Smitha A. and P. Jidesh, Detection of retinal disorders from OCT images using generative adversarial networks, Multimedia Tools and Applications (Springer), https://doi.org/10.1007/s11042-022-12475-1, Vol. 81, pp. 29609–29631, 2022 (3.6),
52. Smitha A., Febin I.P., P. Jidesh, A retinex based non-local Total Generalized Variation framework for OCT image restoration , Biomedical signal processing and control (Elsevier), Vol. 71, pp. 1-16, 2022, (3.88), https://doi.org/10.1016/j.bspc.2021.103234., 2022, (5).
56. S. George, Krishnendu R., Argyros I. K., P. Jidesh, Extending the applicability of Cordero type iterative method, Symmetry -MDPI, 14. https://doi.org/10.3390/sym14122495, Vol. 14, pp. 1-12, 2022 (2.7).
55. Santhosh George, Ramya Sadananda, Jidesh Padikkal, Ioannis K. , On the order of convergence of Noor-Waseem method, Mathematics-MDPI, https://doi.org/10.3390/math10234544, Vol. 10, pp. 1-14, 2022 (2.5).
51. S. Geroge, M. Chitra and P. Jidesh, Finite dimensional realization of a parameter choice strategy for Fractional Tikhonov regularization method in Hilbert scales, Hacettepe Journal of Mathematics and Statistics (Dergipark), 1-24, https://doi.org/10.15672/hujms.1092739, 2022 (1.0),
50. Chitra M. S.George, P. Jidesh, Projection method for fractional Lavrentiev regularisation method in Hilbert Scales, J. Analysis (Springer), https://doi.org/10.1007/s41478-022-00516-9, Vol. 31, 1303–1333, 2022 (0.8)
49. S. George, R. Krishnendu, P. Jidesh, Finite dimensional realization of FTR method with Raus and Gfrerer type discrepancy principle, RCMP (Springer), https://doi.org/10.1007/s12215-022-00858-0, Vol. 72, pp. 3765–3787, 2022, (1.0).
48. S. George, Krishnendu R., P. Jidesh, On Newton's midpoint-type iterative scheme's convergence, International Journal of Applied and Computational Mathematics (Springer), https://doi.org/10.1007/s40819-022-01468-1, Vol. 8., 2022.
50. S. George, P. Jidesh, R. Krishnandu, I. K. Argyros, A new parameter choice strategy for Lavrentiev regularization method for nonlinear ill-posed equations, Mathematics (MDPI), (2.5) https://doi.org/10.3390/math10183365, 2022.
47. S. George, M. Saeed, , I. K. Argyros and P. Jidesh, An apriori parameter choice strategy and a fifth order iterative scheme for Lavrentiev regularization method, Journal of Applied Mathematics and Computing (Springer), (2.4), https://doi.org/10.1007/s12190-022-01782-3, Vol. 69, pp. 1095–1115, 2022.
46. S. George, M. Sayeed, P. Jidesh "On the convergence of Homeier method and its extensions", Journal of Analysis (Springer), https://doi.org/10.1007/s41478-022-00449-3 , Vol. 31., pp. 645–656, 2022 (0.8).
2021
45. Smitha A. and P. Jidesh, A nonlocal deep image prior model to restore Optical Coherence Tomographic images from Gamma distributed speckle noise , J. Modern Optics (Taylor and Francis), Vol. 68(18), pp. 1002-1017, 2021, (1.46) https://doi.org/10.1080/09500340.2021.1968052
44. I.P Febin and P. Jidesh, Despeckling and enhancement of ultrasound images using non-local variational framework, The Visual Computer Journal (Springer), https://doi.org/10.1007/s00371-021-02076-8, Vol. 38, pp. 1413–1426, 2021(3.5)
43. P. Jidesh and et al. Convergence analysis of a fifth order iterative method using recurrence relations and conditions on the first derivative, Mediterranean Journal of Mathematics, In Press (Springer), Vol. 18, 57, 2021, https://doi.org/10.1007/s00009-021-01697-6, (1.2)
42. M. Chitra, S. George and P. Jidesh, Finite dimensional realization of a parameter choice strategy for Fractional Tikhonov regularization method in Hilbert scales, Partial Differential Equations in Applied Mathematics, Vol. 5, https://doi.org/10.1016/j.padiff.2021.100246, 2021.
41. S. George, Shobha M.E., P. Jidesh, Finite dimensional realization of fractional Tikhonov regularization method in Hilbert scales, Partial Differential Equations in Applied Mathematics (Elsevier), Vol. 5,https://doi.org/10.1016/j.padiff.2021.100246, 2021.
2020
40. Chitra M, S. George, P.jidesh, "Fractional Tikhonov regularization method in Hilbert scales", Applied Mathematics and Computation(Elsevier), 392, 1-30, 2021. https://doi.org/10.1016/j.amc.2020.125701, (4.3)
39. Savitha G and P. Jidesh "A Holistic Deep Learning Approach for Identification and Classification of Sub-solid Lung Nodules in Computed Tomographic Scans", Computers and Electrical Engineering (Elsevier), Vol. 84, pp. 1-15, 2020, DOI: https://doi.org/10.1016/j.compeleceng.2020.106626 (4.1)
38. P. Jidesh et al. A Retinex Based Variational Model for Enhancement and Restoration of Low Contrast Remote Sensed Images Corrupted by Shot Noise, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensining, Vo. 13, pp. 941 - 949, 2020. DOI: https://doi.org/10.1109/JSTARS.2020.2975044 (5.5)
37. P.Jidesh and I.P. Febin A perceptually inspired variational model for enhancing and restoring remote sensing images, IEEE Geoscience and Remote Sensing Letters, DOI: https://doi.org/10.1109/LGRS.2020.2969411, Vol 18, 2, 251-255, 2020. (5)
36. Priya K, Kedarnath S, P. Jidesh, Despeckling of SAR images using shrinkage of two-dimensional discrete orthonormal S-transform, International Journal of Image and Graphics (World scientific), Vol. 21, 2021, 1-10. (1)
2019
35. G. Savitha snd P. Jidesh, A fully-automated system for identification and classification of subsolid nodules in lung Computed Tomographic scans, Biomedical Signal Processing and Control (Elsevier), Vo. 53, pp. 1-15, DOI: https://doi.org/10.1016/j.bspc.2019.101586, 2020. (5)
34. P. Jidesh et al, Multiple-Coil Magnetic Resonance Image Denoising and Deblurring With Nonlocal Total Bounded Variation, IETE-Technical Review (Taylor & Francis), https://doi.org/10.1080/02564602.2019.1617202, Vol. 37, No. 3, pp. 309-314, 2019 (2.4)
33. Shubha VS, Santhosh George; Jidesh P, Third-order derivative-free methods in Banach Spaces for nonlinear ill-posed equations, J. Applied Math. and Computing (Springer), Vol. 61, pp. 137–153, 2019. https://doi.org/10.1007/s12190-019-01246-1 (2.4)
2018
32. P. Jidesh et al. Estimation of noise using non-local regularization frameworks for image denoising and analysis, AJSE (Springer), DOI: http://dx.doi.org/10.1007/s13369-018-3542-2. Vol. 44, pp. 3425–3437, 2018 (2.8)
31. Jidesh et al. Noise classification and automatic restoration system using Non-local regularization frameworks, J. Imaging Sciences (Taylor & Francis), Vol. 66, No. 8, pp. 479-491, https://doi.org/10.1080/13682199.2018.1518760 (1)
30. Shivarama Holla and P. Jidesh Non-local total variation regularization approach for image restoration under a Poisson degradation, J. Modern Optics (Taylor and Francis), Vol. 65, No. 19, pp. 2265-2276, 2018, https://doi.org/10.1080/09500340.2018.1506058 (1.7)
29. P. Jidesh and B. Balaji, Adaptive non-local level-set model for despeckling and deblurring of Synthetic Aperture Radar imagery, International Journal of Remote Sensing, (Taylor and Francis), Vol. 39, No. 20, pp. 6540-6556, DOI: https://doi.org/10.1080/01431161.2018.1460510 (3.5)
28. P. Jidesh and Shivarama Holla, Non-local total variation regularization models for image restoration, Computers and Electrical Engineering (Elsevier), Vol. 67, No. 1. pp. 114-133, https://doi.org/10.1016/j.compeleceng.2018.03.014 (4)
27. P. Jidesh and Balaji B., Image despeckling with non-local total bounded variation regularization, Computers and Electrical Engineering (Elsevier), Vol. 70, Pages 631-646, 2018, https://doi.org/10.1016/j.compeleceng.2017.09.013 (4)
2017
26. Ioannis Argyros, P. Jidesh, Santhosh George, Ball Convergence for a third order method based on Newton's method and the Adomian decomposition method, IJCONVC, To appear
25. V.S. Shubha, S. Goerge and P. Jidesh, Convergence of a Tikhonov Gradient type-method for nonlinear ill-posed equations, International Journal of Applied and Computational Mathematics (Springer), To appear.
24. P. Jidesh and Shivaram Holla, Non-local Total Bounded Variation scheme for Multiple-coil Magnetic Resonance Image Restoration, Multidimensional Systems and Signal Processing (Springer), Vol. 29, No. 4, pp 1427–1448, 2018, https://doi.org/10.1007/s11045-017-0510-z (2)
23. Ioannis K. Argyros , Santhosh George and P. Jidesh, Iterative Regularization methods for ill-posed Operator Equations in Hilbert scales, NONLINEAR STUDIES , Vol. 24, No. 2, pp 1-15.
22. Ioannis K. Argyros, Jidesh P. and Santhosh George, Improved robust semi-local convergence analysis of Newton’s method for cone inclusion problem in Banach spaces under restricted convergence domains and majorant conditions, Nonlinear Functional Analysis and Applications, To appear.
21. P. Jidesh, Image despeckling and deblurring via regularized complex diffusion, Signal, Image and Video Processing (Springer), (1.7) Vol. 11, No. 6, pp 977–984, 2017, https://doi.org/10.1007/s11760-016-1047-6
2016
20. V.S. Shubha, S. George and P. Jidesh, Finite dimensional realization of a Tikhonov gradient type-method under weak conditions, J. Rendiconti del Circolo Matematico di Palermo (Springer), Vol. 65, No.3, pp 395–410
19. P. Jidesh et al. , Image Restoration Using Adaptive Region-Wise p-Norm Filter with Local Constraints, International Journal of Image and Graphics (World Scientific Press), Vol. 16, No.2, pp. 1-25.
18. I.K. Argyros, P. Jidesh and Santhosh George, "Ball Convergence for Second Derivative Free Methods in Banach space", International Journal of Applied and Computational Mathematics (Springer), Vol. 3, No. 2, pp 713–720.
2015
17. Vorkady.S.Shubha , Santhosh George , P. Jidesh and M. E. Shobha, Finite dimensional realization of a quadratic convergence yielding iterative regularization method for ill-posed equations with monotone operators, Applied Mathematics and Computation (Elsevier), Vol 273, pp. 1041-1050, https://doi.org/10.1016/j.amc.2015.10.051 (4.3)
16. I. K. ARGYROS, P. JIDESH and S. GEORGE (2015), An Improved Semi-local Convergence Analysis for a Three Point Method of Order 1.839 in Banach Space, Advances in Nonlinear variational Inequalities, Vol.18, No.1, (2015),pp. 23-32.
15. P. Jidesh, Vorkady.S.Shubha and Santhosh George, "A Quadratic Convergence Yielding Iterative Method for the Implementation of Lavrentiev Regularization Method for Ill-posed Equations", Applied Mathematics and Computation (Elsevier), Vol. 254, pp. 148–156, 2015, https://doi.org/10.1016/j.amc.2014.12.090 (4.3)
14. V.S. Shubha , S. George and P. Jidesh, A derivative free iterative method for the implementation of Lavrentiev regularization method for ill-posed equations, Numerical Algorithms (Springer), Vol. 68, No. 2, pp 289-304, 2015, https://doi.org/10.1007/s11075-014-9844-x (2.3)
2014
13. P. Jidesh, "A convex regularization model for image restoration", Computers and Electrical Engineering (Elsevier), Vol. 40, No. 8, pp. 66-78, 2014, https://doi.org/10.1016/j.compeleceng.2014.03.013 (4)
12. P. Jidesh et al. "An image dehazing model considering multiplicative noise and sensor blur", Journal of Computational Engineering (Hindawi), Vol 2014, Article ID 125356, 9 pages, 2014
11. P. Jidesh et al., "Image enhancement under data-dependent multiplicative Gamma noise", Applied Computational Intelligence and Soft Computing (HINDAWI), Volume 2014 , Article ID 981932, 8 pages, 2014.
10. I.K. Argyros, S. George and P. Jidesh, "Inverse free iterative methods for nonlinear ill-posed operator equations", International Journal of Mathematics and Mathematical Sciences (Hindawi), Vol 2014, pp 1-8, 2014.
9. P. Jidesh, et al.“A curvature driven image inpainting approach for high density impulse noise removal”, AJSE (springer), Vol. 39, No. 5, pp. 3691-3713, 2014 [DOI: 10.1007/s13369-014-0983-0]. (2.7)
8. P. Jidesh and S. George, "Gauss Curvature Driven Image Inpainting for Image reconstruction"', J. Chinese Institute of Engineers (Taylor and Francis), Vol37, No.1, pp-122-133, 2014. (0.6)
2012-2013
7. K. Chaudhary and P. Jidesh, P. Sudheendra and Suresh D. Kulkarni “Quantification and Morphology Studies of Nanoporous Alumina Membranes: A New Algorithm for Digital Image Processing”, Microscopy and Micro Analysis (Cambridge University Press), Vol. 19, No. 4, pp. 1061-1072, 2013. (4)
6. K.S. Chaudhari, P. Jidesh and N.K.Udayashankar, "Fabrication of Nanoporous Alumina and Their Structural Characteristics Study Using SEM Image Processing and Analysis", J. Synthesis and Reactivity in Inorganic, Metal-Organic, and Nano-Metal Chemistry (Taylor & Francis), Vol 42. No. 3, pp. 369-375, 2012. (1.5)
5. P. Jidesh and S. George, "Shock Coupled Fourth-order Diffusion for Image Enhancement'", Computers and Electrical Engineering (Elsevier), Vol 38, No. 5, pp. 1262-1277, 2012. (4)
4. P. Jidesh and Santhosh George, "A Time-dependent Switching Anisotropic Diffusion Model for Denoising and Deblurring Images'', Journal of Modern Optics (Taylor & Francis), Vol. 52, No 2, pp. 140-156, 2012. (1.7)
2010-2011
3. P. Jidesh and Santhosh George, "Curvature Driven Diffusion Coupled with Shock for Image Enhancement/Reconstruction", International Journal of Signal and Imaging Systems Engineering , Vol. 4, No. 4, pp. 238 - 247, 2011.
2. P. Jidesh and Santhosh George, ``Fourth-order Variational Model with Local- Constraints for Denoising Images with Textures'', Int. J. Computational Vision and Robotics, Vol 2, No. 4, pp. 330-340, 2011.
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International Conferences
2024-26
24. Nirmal G., P. Jidesh, Crude Oil Price Forecasting Using AI Models for Improved Strategic and Operational Decisions, Accepted for publication in IEEE ETCC 2026, Bangalore.
23. Neeraj Krishnan P K and P. Jidesh MULTI-SPEC: Multi-scale Feature Driven Speckle-constrained Deep Image Prior Model for Sonar Image Despeckling
6th International Conference on Machine Vision & Augmented Intelligence-2026, SNIT , Surat, Accepted for Publication, 2026.
22. Akhil V., Neeraj Krishnan, P. Jidesh, Ultrasound Image Denoising Using Diffusion Guided Deep Image Prior, IEEEConnect-2026, Bangalore.
21. Febin I. P., Bini A. A., P. Jidesh, A Deep Image Prior Backed Fractional-order Retinex Approach for Despeckling and Enhancement of Synthetic Aperture Radar Images, International Conference on Computer Vision and Robotics (CVR 2026), NIT-Goa, Springer Publisher, 2026.
20. P. Jidesh and A. A. Bini, Diffusion driven deep learning framework for restoring and enhancing speckled images, accepted for presentation and publication in International Congress of Mathematicians (ICM) -2026, Philadelphia, USA.
19. I.P. Febin and P. Jidesh, A retinex driven fractional-order regularization model for despeckling and enhancing of Synthetic Aperture Radar images, CVIP 2024, CCIS 2476, pp. 116–130, 2026,
https://doi.org/10.1007/978-3-031-93697-5 _ 9.
2022
18. Shubham Tikle, Jidesh P., Smitha A., "Assessing Damage of Natural Disasters from Satellite Imagery using a Deep learning Model", Accepted for publication, Presented in 7th International Conference on Microelectronics, Electromagnetics and Telecommunications. (ICMEET 2022), Springer-LNEE.
17. A. Hazarika, P. Jidesh, Detection and Classification of Ships using a self-attention Residual Network, IEEE CICT-2022, IIIT Gwallior.
2021
16. A. Hazarika, A. Smitha and P. Jidesh, Comparative analysis of machine learning and deep learning models for ship classification from satellite images, CVIP-2021, IIT Ropar, Springer Publications, Accepted for publication.
15. A. Smitha, P. Jidesh, J. Jothi Balaji, Vasudevan Lakshminarayanan, Development and validation of a novel automated method for quantification of choroidal thickness in age-related macular degeneration," Proc. SPIE"11842, Applications of Digital Image Processing XLIV, 118422E (1 August
2021); doi: 10.1117/12.2594557
14. I. P. Febin, P. Jidesh, A Fast Computing Model for Despeckling Ultrasound Images. In: Computational Sciences - Modelling, Computing and Soft Computing. CSMCS 2020 (NITC). Communications in Computer and Information Science, vol 1345. Springer, Singapore. https://doi.org/10.1007/978-981-16-4772-7_17
2020
13. P. Jidesh, A Graph Spectral Approach for Restoring Images Corrupted by Shot-noise, (CVIP- IIT Allahabad, Proceedings: AISC Springer)
12. A. Smitha and P. Jidesh, A semi-supervised Generative Adversarial Network for Retinal Analysis from Fundus images, (CVIP- IIT Allahabad, Proceedings: AISC Springer)
11. I.P. Febin and P. Jidesh Fast Computing Models for Despeckling Ultrasound Data, CSMCS-2020 (NIT Calicut), Proceedings (AISC-Conference series)
2019
10. Smitha A., P. Jidesh, Retinal vessel classification using the non-local retinex method, Proceedings of IHCI-2019, IIIT Allahabad (LNCS-Springer).
2017
9. Balaji B and P. Jidesh, Non-local Gradient Fidelity Model for Multiplicative Gamma Noise Removal, ICAPR-2017, ISI Bangalore, IEEE proceedings.
8. Savitha G and P. Jidesh, Lung Nodule Identification and Classification from Distorted CT Images for Diagnosis and Detection of Lung Cancer, MISP-2017, IIT Indore.
Proceedings by springer
2013-2014
7. P. Jidesh, "A shock coupled image enhancement filter for data-dependant multiplicative noise removal" Accepted for presentation at International Congress of Mathematicians (ICM-2014) held at Seoul, S. Korea, during 13th-21st August 2014.
6. P. Jidesh , "A complex diffusion driven approach for removing data-dependent multiplicative noise", Accepted in PReMI (LNCS), Held in ISI, Kolkata, Dec-2013, pp. 284-289.
2010-2011
5. P. Jidesh and Santhosh George, "Shock coupled Coherence Enhancing Diffusion for Robust Core-point Detection in Fingerprints'', Proceedings of the IEEE International
Conference on Pattern Recognition and Intelligent Robotics (ICPAIR), pp. 19-24, June 2011, (UKM-Malaysia).
4. P. Jidesh and Santhosh George, ``Steganalysis: Using the blind deconvolution to retrieve the hidden data'', Proceedings of IEEE International Conference on Network and
Computer Science, pp. V5:68-71, April 2011, (Kanyakumari, India).
3. P. Jidesh and Santhosh George, "Fourth-order Gauss Curvature Driven Diffusion for Image Denoising'', Proceedings of IEEE International Conference on Signal Acquisition
and Processing, pp. V1:260-264, Feb 2011 (Singapore).
2. P. Jidesh and Santhosh George,``A Two-way Tikhonov regularization method for image/signal reconstruction', Proceedings of International Conference on Mathematical
Modeling and Applications to Industrial Problems, Mar, 2011, NIT- Calicut.
1. Bini A.A, M.S Bhat and P. Jidesh, "An Adaptive Total Variation Model with Local Constraints for Denoising Partially Textured Images'', Proceedings of IEEE International
Conference on Graphics and Image Processing, pp. 179-183, Dec 2010, (Manila,Philippines).
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