Automatic Protection of Clothes From Rain

EasyChair Preprint 12341

Abstract

The project "Tender Coconut Type Detection and Classification System using TCNN and 
also find the glucose level of the tender coconut using Laplacian of Gaussian (LoG) Edge Detection" 
aims to develop an automated system for detecting and classifying different types of tender coconuts 
based on their external characteristics using a combination of the Laplacian of Gaussian (LoG) edge 
detection algorithm and TCNN, and provide a recommendation for the appropriate glucose level 
based on the estimated size.The TCNN model will be used to classify the tender coconuts into 
different types based on their external characteristics. Laplacian of Gaussian (LoG) edge detection 
algorithm will also be developed to estimate the size of tender coconuts based on their external 
characteristics, such as diameter, height, and weight. The Laplacian of Gaussian (LoG) edge 
detection algorithm will be used to estimate the glucose level of the tender coconut based on the 
images of the external characteristics. A recommendation system will be developed to provide 
guidance on the appropriate glucose level based on the estimated size of the tender coconut and 
established standards and guidelines.

Keyphrases: Agricultural Technology, Biometrics, Coconut Classification, Convolutional Neural Networks (CNNs), Ethical AI, Healthcare Applications, Transfer Learning, computer vision, data preprocessing, data privacy, deep learning, feature engineering, food science, glucose prediction, image classification, machine learning, model integration, neural networks, predictive modeling, regression analysis

@booklet{EasyChair:12341,
  author    = {Nirmala Selvi and Shenbagalaxmi and K Anjana},
  title     = {Automatic Protection of Clothes From Rain},
  howpublished = {EasyChair Preprint 12341},
  year      = {EasyChair, 2024}}