An Application for Automated Diagnosis of Facial Dermatological Diseases

ABSTRACT Objective: Dermatological diseases are public health problems. Several factors including subjective diagnosis, lack of enough dermatologists, inability to go to a dermatologist due to old age, psychological problems or pandemic like coronavirus enforce to use automated techniques in dermatology. In the literature, there are many techniques on automated lesion classification to provide accurate, objective, reliable and reproducible results for the diagnosis of several dermatological diseases. However, although the techniques are promising, they become useless without a user interface ...Daha fazlası

A Flower Status Tracker and Self Irrigation System (FloTIS)

Rumeysa KESKİN | Furkan GÜNEY | M. Erdal ÖZBEK

The Internet of Things (IoT) provides solutions to many daily life problems. Smartphones with user-friendly applications make use of artificial intelligence solutions offered by deep learning techniques. In this work, we provide a sustainable solution to automatically monitor and control the irrigation process for detected flowers by combining deep learning and IoT techniques. The proposed flower status tracker and self-irrigation system (FloTIS) is implemented using a cloud-based server and an Android-based application to control the status of the flower which is being monitored by the local ...Daha fazlası

Sentiment Analysis Of Online Hotel Reviews Using Machine Learning Methods

Dilara Ceren Moral

This project shows a Python-based Natural Language Processing (NLP) study of online hotel reviews. This study's goal was to do sentiment analysis on a dataset derived from TripAdvisor user reviews that was obtained through the Kaggle platform. In this NLP study, deep learning methods, TensorFlow, and Sklearn were the key libraries used. Machine learning models, such as Logistic Regression, were created and tested for sentiment analysis. A deep learning model built on TensorFlow was further used. The most accurate classifier was the Logistic Regression model, which on the training set had an ac ...Daha fazlası