[HTML][HTML] Accelerated and Precise Skin Cancer Detection through an Enhanced Machine Learning Pipeline for Improved Diagnostic Accuracy

SMMR Swapno, SMN Nobel, PK Meena, VP Meena… - Results in …, 2025 - Elsevier
Unrepaired DNA damage in skin cells causes mutations leading to skin cancer, a highly
aggressive malignancy. This study proposes a machine learning (ML)-based framework for …

[HTML][HTML] XAI-FruitNet: An explainable deep model for accurate fruit classification

S Sultana, MAM Tasir, SMN Nobel, MM Kabir… - Journal of Agriculture …, 2024 - Elsevier
In agricultural technology, precise fruit classification is essential yet challenging due to
inherent interclass similarities and intra-class variabilities among fruit species. Despite their …

ViT-SENet-Tom: machine learning-based novel hybrid squeeze–excitation network and vision transformer framework for tomato fruits classification

SMMR Swapno, SMN Nobel, MB Islam… - Neural Computing and …, 2025 - Springer
Tomatoes are essential fruits in numerous nations for their vast demand. It is very important
to maintain the freshness of tomatoes. One of the primary challenges in the recent culinary …

User Plane Function (UPF) Allocation for C-V2X Network Using Deep Reinforcement Learning

P Sasithong, T Sanguanpuak, P Vanichchanunt… - IEEE …, 2024 - ieeexplore.ieee.org
In this paper, we proposed an online learning method for predicting an allocation of User
Plane Function (UPF) in Cellular Vehicle-to-Everything (C-V2X) networks integrated with …

Multi-task reinforcement learning based on parallel recombination networks

M Liu, Q Zhang, W Qian - IEEE Access, 2024 - ieeexplore.ieee.org
Multi-task Reinforcement learning is a key current trend in the field of reinforcement learning.
It can accomplish multiple tasks using a single network, which is superior to single-task …

[PDF][PDF] Results in Engineering

SMMR Swapno, SMN Nobel, PK Meena, VP Meena… - researchgate.net
Unrepaired DNA damage in skin cells causes mutations leading to skin cancer, a highly
aggressive malignancy. This study proposes a machine learning (ML)-based framework for …