Rupesh Kumar Mishra

Hybrid Feature Extraction and Classification for Conjunctiva-based Anemia Screening

Gourishetty Sindhusha, Rupesh Kumar Mishra, Jegadeesan R

Anemia is still a significant worldwide health problem, especially in low-resource environments with restricted availability of laboratory-based blood assays. This study proposes a non-invasive, image-based anemia screening system with conjunctiva images and ensemble deep learning. The proposed method combines three pre-trained CNNs, …

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A Robust Deep Learning Approach to Tomato Plant Disease Classification Using Resnet-50

Bhagya Laxmi. B, Rupesh Kumar Mishra

Technological advances have contributed significantly to the control of plant diseases. A way to solve the problem in identifying plant diseases is to use deep learning for digital image processing. Global nutrition security and sustainable agriculture depend on the quick and accurate …

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A comprehensive literature review on the detection of tomato leaf disease by deep learning and machine learning models

Bhagya Laxmi.B, Rupesh Kumar Mishra, Gireesha.D

In so far as everyone needs food, farming helps to provide for this basic requirement. Despite making up only 15.4% of the country's GDP, the agriculture sector is crucial to India since it creates a large number of job possibilities. In addition …

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Detection of Iron Deficiency Anemia Using Convolutional Neural Networks Based on Conjunctival Pallor Images

Gourishetty Sindhusha, Rupesh Kumar Mishra, Jegadeesan R

Anemia is a major public health problem, especially in children, which can be diagnosed using invasive blood examinations that are expensive and not feasible in low-resource environments. The present study introduces a non-invasive anemia prediction system via conjunctival images that is safer …

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Ensemble Deep Feature Fusion for Noninvasive Anemia Classification using Conjuctiva Images

Gourishetty Sindhusha, Rupesh Kumar Mishra, R Jegadeesan

As a Major public health issue, anemia affects more than two billion people around the globe. Many resource-constrained environments lack well-equipped labs, which are necessary for many conventional diagnostic techniques which depend on invasive blood testing. This paper presents a noninvasive, image-based …

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Enhanced Crop Disease and Pest Detection Using Adaptive Neuro-Fuzzy Systems with ResNeXt Architecture

Konda Mamatha, Rupesh Kumar Mishra

Crop pests and diseases are responsible for almost 40% of the loss in world agriculture; thus, their early and accurate detection is vital. An Adaptive Neuro-Fuzzy Inference System (ANFIS) with ResNeXt architecture is presented in this paper to improve crop disease and …

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Mitigating Cyber Threats Through Artificial Intelligence with a Deep Dive into Machine Learning Applications in Cyber Security

Shilpa Choudhary, Kodi Srinivas, Rupesh Kumar Mishra, Bhavana Majji et autres

In the digital era, cyber threats are evolving day by day and traditional solutions become ineffective. To overcome this problem, we need adaptive, intelligent protection mechanisms in cybersecurity. This research paper presents a hybrid machine learning method that integrates Convolutional Neural Networks …

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A Unified Framework for Fake News Detection using Content Community and Propagation Features

Sabitha Musuku, Rupesh Kumar Mishra

Social media means pose a serious threat to social trust, democracy, and the discourse that occurs in the society through various efforts to broadcast fake news. Traditional fake news detection systems often rely solely on content-based features, making them highly susceptible to …

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A Systematic and Analytical Review on Drowsiness Detection System-based Real-Time Application

Anshu Kumar Dwivedi, Vishwanath Bijalwan, Rupesh Kumar Mishra

Drowsiness detection is a method that detects drowsiness in drivers. Driver drowsiness and careless driving are the causal factors of traffic crashes, resulting in the loss of innocent lives and affecting road transportation efficiency. Several drowsiness detection systems have been introduced, each …

Plant leaf disease detection and classification using CNN and VGG16 models

Bhagya Laxmi, Rupesh Kumar Mishra

Our lives are greatly impacted by the agricultural sector.The most significant industry in our economy is agriculture.The result of effective management is a successful agricultural product.Farmers that are unaware of leaf disease produce less.Profit and loss are determined by production, hence identifying …

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Meta-heuristic Ant-Bee colony algorithms for dynamic big data analysis in real-time

Gayatri Tavva, Rajesh Sura, Divyesh Shah, Rohit Kommareddy et autres

To overcome this problem, a new optimization method called the Meta-Heuristic Ant-Bee Colony Algorithms (MH-ABC) has been proposed that uses the collective behavior of both ants & bees to effectively gather, process, and analyze dynamic big data in real-time. The Ant and …

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Sentiment and Semantic Embeddings for Disaster Decision-Making

Rupesh Kumar Mishra

The popularity of social media and public opinions in online news channels are attracting the attention of government to help for finding out better private/public companies for efficient disaster management. The obtained accuracy was around 60% due to the lack of information …

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