Dr Bappaditya Mandal's Outputs (5)

Perturbed Composite Attention Model for Macular Optical Coherence Tomography Image Classification (2021)
Journal Article
Mishra, S. S., Mandal, B., & Puhan, N. B. (2022). Perturbed Composite Attention Model for Macular Optical Coherence Tomography Image Classification. IEEE Transactions on Artificial Intelligence, 3(4), 625-635. https://doi.org/10.1109/tai.2021.3135797

In this article, we propose a deep architecture stemming from a perturbed composite attention mechanism with the following two novel attention modules: Multilevel perturbed spatial attention (MPSA) and multidimension attention (MDA) for macular optic... Read More about Perturbed Composite Attention Model for Macular Optical Coherence Tomography Image Classification.

Stand-Alone Composite Attention Network for Concrete Structural Defect Classification (2021)
Journal Article
Bhattacharya, G., Puhan, N. B., & Mandal, B. (2022). Stand-Alone Composite Attention Network for Concrete Structural Defect Classification. IEEE Transactions on Artificial Intelligence, 3(2), 265-274. https://doi.org/10.1109/tai.2021.3114385

Interleaved Deep Artifacts-Aware Attention Mechanism for Concrete Structural Defect Classification. (2021)
Journal Article
Mandal, B. (2021). Interleaved Deep Artifacts-Aware Attention Mechanism for Concrete Structural Defect Classification. IEEE Transactions on Image Processing, 6957 - 6969. https://doi.org/10.1109/TIP.2021.3100556

Automatic machine classification of concrete structural defects in images poses significant challenges because of multitude of problems arising from the surface texture, such as presence of stains, holes, colors, poster remains, graffiti, marking and... Read More about Interleaved Deep Artifacts-Aware Attention Mechanism for Concrete Structural Defect Classification..

Deep Regularized Discriminative Network (2021)
Journal Article
Mandal, B. (2021). Deep Regularized Discriminative Network. https://doi.org/10.1007/s42979-021-00647-z

Traditional linear discriminant analysis (LDA) approach discards the eigenvalues which are very small or equivalent to zero, but quite often eigenvectors corresponding to zero eigenvalues are the important dimensions for discriminant analysis. We pro... Read More about Deep Regularized Discriminative Network.

GlaucoNet: Patch-Based Residual Deep Learning Network for Optic Disc and Cup Segmentation Towards Glaucoma Assessment (2021)
Journal Article
Mandal, B. (2021). GlaucoNet: Patch-Based Residual Deep Learning Network for Optic Disc and Cup Segmentation Towards Glaucoma Assessment. https://doi.org/10.1007/s42979-021-00491-1

Glaucoma is a chronic eye condition causing irreversible vision damage and presently stands as the second leading cause of blindness worldwide. Damaged optic disc and optic cup assessment in color fundus image has been shown to be a promising method... Read More about GlaucoNet: Patch-Based Residual Deep Learning Network for Optic Disc and Cup Segmentation Towards Glaucoma Assessment.