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Author

B. N. Anoop

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#explainable ai Open access Oct 2026

A deep learning-based plant disease classification using image recognition techniques

Plant diseases significantly threaten global food security, necessitating accurate and automated diagnostic systems. This work presents a modular deep learning framework for systematic benchmarking and comparative analysis of multiple architectures using the PlantVillage dataset. The framework integrates pretrained m...

B. Anoop, K. Sujesh, Ramyashree et al. · 0 citations
Open access Sep 2026

Automated classification and segmentation of brain abnormalities using deep learning approaches in brain MRI

Accurate classification and segmentation of brain tumors from Magnetic Resonance Imaging (MRI) are essential for early diagnosis, treatment planning, and clinical decision-making. However, manual interpretation of MRI scans is time-consuming and prone to inter-observer variability. Deep learning techniques have emerged...

Rashmitha R. Nayak, Ramyashree, S. Raghavendra et al. · 0 citations
Open access Aug 2026

A comparative evaluation of deep learning architectures, loss functions, and ensemble strategies for underwater fish species classification

The experimental results indicate that class-weighted cross-entropy loss consistently provided stronger performance for individual models, whereas focal loss produced a marginal improvement when used with the soft-voting ensemble.

Prithvi Shenoy, Ramyashree, S. Raghavendra et al. · 0 citations
Open access 2026

Effective Deep Learning Framework for Retinal Abnormality Detection in OCT Imaging

The results demonstrate that the proposed models, particularly EfficientNetV2B2 and Swin Transformer, exhibit high classification accuracy and strong generalization across datasets support the viability of deep learning in real-time OCT-based retinal disease screening.

Manan Mathur, S. Niyas, Vipin Venugopal et al. · 0 citations
Open access 2026

Efficient Interactive Image Segmentation Using Multilayer Perceptron

A novel IIS framework based on Multi-Layer Perceptron (MLP), which fuses clicks from users with feature representations extracted from the Transformer Encoder, which closes the gap between interactive user instructions and deep learning and provides a practical and flexible solution for accurate segmentation in many ap...

S. Raghavendra, Rithika Shyam Kumar, S. Abhilash et al. · 0 citations

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