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

BOON

,Waste Classification Based on Computer Vision Using Deep Learning Models and Public Awareness,: MobileNetV3 increased to 82%, InceptionV3 to 89%, and ResNet50 to 90%. These findings underscore the EcoQuest Application’s efficacy in enhancing waste management practices, contributing to a more sustainable and environmentally conscious future.

Tailor

Travel Mitra: An AI Assisted Tour Companion,ans that are tailor-made for you, and keeping you updated with the most current information. This paper goes into how the chatbot works, how it figures out what you need, and how well it does its job based on what people who’ve used it say.

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放弃

多骨

Predictive Modeling for Ischemic Stroke Using Machine Learning,s-Validation, which improves precision and contributes greatly to stroke research and therapeutic applications. The suggested method excels in precise ischemic stroke subtype classification, with high metrics such as accuracy 0.98, precision 0.94, recall 0.96, and F1 score 0.98, all with an efficien

Arteriography

Blind Image Blur Type Estimation and Image Deconvolution Techniques,pares various linear and nonlinear restoration methods. The Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR), assessment of blur, and forms of blur were the basis for the analysis and comparison.

cortisol

Comparative Analysis of Neural Networks with Traditional ML Algorithms for Crime Prediction,ral Networks are the four models selected for comparison in the proposed work. The obtained results include the training time needed for each model, along with its accuracy, precision, recall, and F1 score. As recall is the ratio of the number of arrest cases correctly predicted by the model to the

不理会

背带

genuine

Disease Segmentation in Groundnut Crop Leaves Using Image Processing Techniques, In the next phase, to enhance the segmentation result, the nonlinear noise reduction filter is analysed with different sigma values and the appropriate value (σ = 4) is fixed. It produced enhanced segmentation results with noise-less images. To check the generalization ability of the LSDDGNL, it is