Manoj Diwakar

Multi-scale gated transformer-EfficientNet fusion model for Alzheimer’s disease diagnosis

Upendra Singh, Vidit Kumar, Bhaskar Pant, Manoj Diwakar et autres

RETRACTED: Diwakar et al. Low-Dose COVID-19 CT Image Denoising Using Batch Normalization and Convolution Neural Network. Electronics 2022, 11, 3375

Manoj Diwakar, Prabhishek Singh, Girija Rani Karetla, Preeti Narooka et autres

The journal retracts the article titled “Low-Dose COVID-19 CT Image Denoising Using Batch Normalization and Convolution Neural Network” [...]

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Generative Adversarial framework for CT image denoising using Self-Attentive Residual UNet and Patch GAN Discriminator

Swapna Katta, Prabhishek Singh, Deepak Garg, Manoj Diwakar

Computed Tomography (CT) is an indispensable tool to identify various health conditions. In Low Dose (LDCT) imaging, lower radiation is frequently chosen to minimize the impact of radiation on the human body, but it results in degraded image quality and subsequently generates …

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Multimodal Visible - Infrared Fusion for Robust Human Action Recognition

Aditya Balodi, Manoj Diwakar, Neeraj Kumar Pandey, Aditya Joshi et autres

Human activity recognition that is truly robust to a wide variety of environments will have to depend on the effective use of the different modalities in a complementary way. On one hand, visible-spectrum imagery gives texture and appearance details; on the other …

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Correction: Multimodality medical image fusion using directional total variation based linear spectral clustering in NSCT domain

Mohammad Zubair Khan, Manoj Diwakar, Prakash Srivastava, Prabhishek Singh et autres

In the original version of this Article, Mohammad Mahyoob Albuhairy was omitted as a corresponding author. Correspondence and requests for materials should also be addressed to: mqassem@taibahu.edu.sa.

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A switching-based deep learning framework for personalized and adaptive E-commerce recommendations

Kapil Saini, Ajmer Singh, Manoj Diwakar, Prabhishek Singh et autres

In recommendation systems, it is bit challenging to address diverse user profiles, particularly when users demonstrate varied interaction histories and preferences. These chalenges include data sparsity and the cold start problem which requires the innovative solutions to ensure precise and efficient recommendations. …

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A Review on LULC Change Detection Using Machine Learning Algorithms in Google Earth Engine

Navneet Kaur, Rishi Prakash, Manoj Diwakar, Anurag Vidyarthi

Across different geographic regions machine learning algorithms implemented in Google Earth Engine showed the OA (Overall Accuracy) ranging from 80 to 97% for Land Use/Cover change detection. With an accuracy spanning from 90% to 96%, the Random Forest method proved reliable across …

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A Temperature-Scaled and Direction-Consistent Softmax Framework for Multimodal Medical Image Fusion

Siddham Jain, Vikram Yadav, Prabhishek Singh, Shailesh Bhosekar et autres

In this paper, a novel multimodal medical image fusion (M3IF) strategy (SWT-TSSF-DCS) that incorporates Stationary Wavelet Transform (SWT) and Temperature-Scaled Softmax Fusion (TSSF) for low-frequency (LF) coefficients and Direction-Consistency Softmax (DCS) for high-frequency (HF) coefficients is proposed. SWT-TSSF-DCS is compared with some …

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Laplacian Pyramid-Based Fusion with Contrast–Entropy Attention and Sign-Consistent Softmax for Enhanced Multimodal Medical Imaging

Mohammed Rafiq, Ankur Maurya, Prabhishek Singh, Manoj Diwakar

Medical image fusion (MIF) helps in understanding and diagnosis of medical images by fusing the information from multimodal medical modalities such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). The traditional transform methods are not that great in fusing the low-frequency …

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Variance-Entropy Guided SWT Fusion with P-Sharpened Softmax for Enhanced Medical Imaging

Mohammed Rafiq, Ankur Maurya, Prabhishek Singh, Manoj Diwakar

The primary goal of medical image fusion (MIF) is to combine important medical information from different medical modalities, including computed tomography (CT) and magnetic resonance imaging (MRI), into a single image. This research paper proposes a novel MIF method that integrates Stationary …

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A Deep Learning Architectures for Liver Disease Detection: From CNNs to Transformers and Beyond

Pranjal Kaushik, Himanshu Vashishtha, Neeraj Kumar Pandey, Manoj Diwakar et autres

Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD), previously referred to as Non-Alcoholic Fatty Liver Disease (NAFLD), is currently established as the world’s most prevalent chronic liver disease. MAFLD impacts almost 25 to 30% of the world’s population. The condition has the potential to …

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Multimodality medical image fusion using directional total variation based linear spectral clustering in NSCT domain

Mohammad Zubair Khan, Manoj Diwakar, Prakash Srivastava, Prabhishek Singh et autres

In medical science, there is a challenge to find out critical information from the medical images by low vision disability medical experts. As a solution, we can enhance the medical images by fusing different modality images viz., CT-MRI which can be more …

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