10 Computer Science Projects for engineering students.(CSE) 1) Machine Learning approach for musical therapy using facial expressions
10 Computer Science Projects for engineering students.(CSE)
1) Machine Learning approach for musical therapy using facial expressions
In this project we detect all different types of emotions, it is quite natural that human emotions have a direct relationship with a particular music genre. By looking at facial expressions we can gauge if a person is feeling happy, sad, angry, scared, depressed, or tender. Humans’ emotions can be altered by music, which may also have an impact on their mood and health.
Research has proved that we can cure some illnesses using music therapy, in this project we have designed an intelligent system that organises a music collection based on the genres each song conveys and then recommends a well-suited music playlist to the psychiatrist for the patients based on their facial expressions is created by the combination of musical therapy and facial emotion detection.
The picture is put through facial recognition and emotion recognition.the patients’ techniques. The tunes that go with The greatest playlist for this emotion is then suggested. results in calming and relaxing patients.
2. Dynamic traffic management system based on IoT and image processing
Traffic management has become a major issue in most of metro cities due to the growth of population and increase in the number of vehicles on the road. The manual system is cumbersome and ineffective. In this project, we have used an adaptive traffic control system by using image processing and the Internet of Things (IoT).
In this system we have used image processing to examine real-time data and cameras are deployed to continuously monitor the various lanes, with an image processing algorithm to find and count the number of vehicles in each lane that has been sent to the central processing unit.
waiting time has been calculated using the algorithm based on the number of vehicles which further improves the traffic flow efficiency by decreasing the average waiting time. The technology is also effective in emergency scenarios and lessens pollution from CO2 emissions, making it an Internet of Things-based adaptive traffic management system (IoT).
3. ML Project-Classification of Cancerous Profiles
There are multiple factors to treat cancer of options available for cancer treatment. The type of treatment recommended for an individual is influenced by various factors such as cancer type, the severity of cancer (stage) and most important the genetic heterogeneity. In such a complex environment, the targeted drug treatments are likely to be irresponsive or respond differently.
To study anticancer drug response, we need to understand cancerous profiles. These cancerous profiles carry information that can reveal the underlying factors responsible for cancer growth. Hence, there is need to analyze cancer data for predicting optimal treatment options.
Analysis of such profiles can help to predict and discover potential drug targets and drugs. In this paper the main aim is to provide machine learning based classification technique for cancerous profiles.
