Titlebook: Machine Learning, Image Processing, Network Security and Data Sciences; 5th International Co Naveen Chauhan,Divakar Yadav,Jorge Morato Lara

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Detection and Classification of Waste Materials Using Deep Learning Techniquesues. Object detection and classification algorithms use machine learning to produce meaningful results. Thus, in real-life following this approach we can get benefits of enhanced performance in waste identification and increase in recycled materials. We review existing research and solutions for was

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A Comparative Analysis of ML Based Approaches for Identifying AQI Level cities, with a particular focus on enhancing air quality in Asian nations such as India. Over the recent years, the utilization of machine learning (ML) techniques has experienced a substantial surge in popularity for predicting the AQI. The primary goal of this work is to assess the air quality le

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Marker-Based Augmented Reality Application in Education Domaint more interactive and engaging. One way that augmented reality can be used in education is through the use of AR-based applications and educational games that allow students to interact with virtual objects and environments in the real world. These applications can be used to teach subjects such as

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Phishing Detection Using 1D-CNN and FF-CNN Models Based on URL of the Websiteon. However, this convenience comes with a significant risk to user security. Web users are exposed to various types of cyberattacks, such as Phishing, malware, profiling, etc. These hazards have the potential to compromise individuals or organizations and deny lists. The traditional Phishing defens

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Diabetes Prediction Using Machine Learning Classifiersulin or does not use the insulin that it does produces adequately. Insulin is a hormonal substance that regulates glucose levels in blood. Hyperglycaemia refers to high blood sugar levels, commonly known as blood glucose. It can lead to serious health consequences in diabetics over time. This condit

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The Potential of 1D-CNN for EEG Mental Attention State Detectionnterfaces (BCIs). However, the current biggest challenge in BCI research is the accurate classification of EEG signals. The old methods, such as visual assessment, were neither standardised or statistically analysed. Because of these limitations, many techniques have been created to quantify and ext