Automating the Machine Learning Process using PyCaret and Streamlit

N Sarangpure, V Dhamde, A Roge… - … for Innovation in …, 2023 - ieeexplore.ieee.org
Machine learning applications for the industry have seen significant growth and attention in
recent years. As a result, there is a significant need for Machine learning engineers across …

Satellite image segmentation for forest fire risk detection using gaussian mixture models

AA Deshmukh, SDB Sonar, RV Ingole… - … on Applied Artificial …, 2023 - ieeexplore.ieee.org
Forest fires are a major threat to the environment, causing destruction to both wildlife and
human habitats. Despite preventative measures, they still contribute significantly to global …

Cryptocurrency Price Analysis using Deep Learning

P Negi, R Dhawad, NC Morris… - … Computing and Smart …, 2023 - ieeexplore.ieee.org
Crypto currency is an immerging field for investments and trading which attracts many
businessmen, investors, and most importantly a generation of aspiring youth which …

Flood extent mapping with unmanned aerial vehicles data using deep convolutional neural network

V Barkhade, S Mahakarkar, R Agrawal… - … and Smart Systems …, 2023 - ieeexplore.ieee.org
Flooding is a common occurrence that results in human fatalities, severe environmental
harm, and major infrastructural damage. A method for mapping areas with apparent and …

Enhancing Plant Health through Deep Neural Network based Leaf Disease Detection

RV Ingole, SS Nikhate, R Agrawal… - … on Applied Artificial …, 2023 - ieeexplore.ieee.org
Farming is a vital industry that not only provides food but also raw materials for numerous
industries while contributing significantly to the economy. Plant diseases and infestations …

Design of Autonomous Weed Elimination using Maching Learning Techniques

A Giradkar, R Adpawar, R Agrawal… - … and Smart Systems …, 2023 - ieeexplore.ieee.org
The abstract presents a system that employs deep learning techniques to automatically
detect weeds in agricultural fields. While the system's efficiency in identifying the presence of …

Speech Emotion Recognition using Dialogue Emotion Decoder and CNN Classifier

SN Atkar, R Agrawal, C Dhule… - … on Applied Artificial …, 2023 - ieeexplore.ieee.org
Recently, everywhere in the world for the purpose of recognizing the emotions research are
carried out. Understanding a person's true state at the time they are uttering words is the first …

Smart AI based Eye Gesture Control System

P Jaiswal, M Dhakite, C Dhule… - … and Control Systems …, 2023 - ieeexplore.ieee.org
There are many people who are physically disabled or paralyzed due to some accident,
because of which they are unable to do their everyday activities such as watching shows …

Machine Learning Algorithm Comparison for Traffic Signal: A Design Approach

S Deshmukh, A Parwekar, B Danej… - 2023 8th …, 2023 - ieeexplore.ieee.org
The number of vehicles is increasing significantly every day, especially in major cities. To
control traffic flow on extensive road networks and facilitate crossing traffic flow on extensive …

Extracting Urban Built-up Areas from Optical and Radar Data Fusion using Machine Learning Algorithms

W Woreket, GA Zeleke - International Journal of Image and Data …, 2024 - Taylor & Francis
Accurate and up-to-date information on urban built-up areas is significant for managing
urban growth and development. Earth Observation (EO) data are valuable sources for …