Titlebook: Innovations and Advances in Cognitive Systems; ICIACS 2024, Volume S. D. Prabu Ragavendiran,Vasile Daniel Pavaloaia,A Conference proceedin

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Empowering Early Autism Detection in Toddlers Using Deep Neural Networks,izes Deep Neural Networks (DNN) to extract complex patterns and meaningful features from extensive datasets to enable early autism detection. This research utilizes a diverse dataset encompassing facial images of children and behavioral characteristics sourced from online platforms. Various Deep Neu

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Comparative Analysis of Neural Networks with Traditional ML Algorithms for Crime Prediction,ome essential due to the rise in crime rates worldwide. This would help the authorities to better allocate resources and prevent such incidents, thereby helping to drop crime rates. This research aims to perform a comparison of a few traditional machine learning (ML) models with neural networks (NN)

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Carcinoma Detection Using Deep Learning,ural Networks (CNNs), Visual Geometry Group-16 (VGG-16), and Visual Geometry Group-19 (VGG-19). The primary objective is to accurately classify CT scan images into four distinct categories: Adenocarcinoma, Large cell carcinoma, Squamous cell carcinoma, and normal lung tissue. In addition to model de

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Comparative Analysis of CNN, Xception and Inceptionv3 for Classifying Tuberculosis, Pneumonia Normaecessary medical scans, possibly due to weather changes or other factors. Some diseases or issues can be linked to specific organs or parts of the human body. For instance, a deep learning model can use chest X-ray images to classify conditions such as pneumonia, tuberculosis, or other diseases. Thi

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,A Two Layer Hybrid Approach for Parkinson’s Disease Detection Optimized via Modified Metaheuristic ve dysfunction and, in some cases, dementia. While no cure is available yet, early detection and treatment do have an immense impact on the quality and length of life. Since the symptoms are hard to detect in the early stages, applying machine learning can enhance the diagnostics. Long short-term me

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Comparative Analysis of Machine Learning Algorithms for Elevation Dataset Regression,. A thorough regression analysis on elevation datasets utilizing Support Vector Machines (SVM), k-Nearest Neighbors (KNN), Random Forest, and Decision Tree algorithms is conducted. The research study aims to evaluate their effectiveness of different algorithms in predicting the elevation values acro

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Disease Segmentation in Groundnut Crop Leaves Using Image Processing Techniques,The primary disease which affects groundnut crop growth and cultivation is leaf spot. Several crop disease management approaches exist. But those are time-consuming, require human interventions, economically ineffective and less scalable. Therefore there is a need for an appropriate approach to reso