Information technology (IT), computer science engineering (CSE), and computer science are all names for studying and developing computer software. You won’t find a motivating resource for aspiring computer scientists and IT professionals anywhere else. This repository stores CSE and IT majors’ future and historical efforts.
As a result, it compiles a repository of cutting-edge concepts for future artificial intelligence projects in computer science and IT. Familiarity with robot differences and similarities is helpful before delving deeper into artificial intelligence research.
Seniors in engineering and information technology programs: if you want to know which five AI project ideas have the most potential, you’ve found the proper place.
Computer Vision For Vehicle Counting And Identification
People move to cities so they may be closer to services such as those provided by schools, hospitals, and places of work. Many of the world’s major cities have severe congestion problems.
As the population has grown, additional roads have had to be built, which has decreased the current system’s effectiveness. Most major cities suffer from traffic congestion because there aren’t enough roads to accommodate the number of cars on the road. There will be additional cars on the road as the urban population grows.
Using public transportation is similar to putting in place a system that can identify and tally individual automobiles for intelligent transportation and traffic management, for example. Lack of access to live traffic data contributes to ineffective traffic management.
Drunk Driver Detection System
According to the World Health Organization, about 1.3 million individuals died in traffic-related events in 2018. (WHO).
According to the annual report on road deaths published by the National Freeway Traffic Safety Administration (NHTSA), 91,000 individuals were killed in vehicle accidents involving drowsy drivers in 2017, while 795 people died from exhaustion.
Weak or sleepy motorists are a common contributor to traffic mishaps. Researchers have shown that drivers’ energy and steering abilities decline after two or three hours on the road.
Lunchtime, early afternoon, and late night all pose the same risks. One’s drowsiness may be mistaken for fatigue if it occurs while one is engaged in some activity.
The Driver Drowsiness Detection System may evaluate three states of alertness in this manner: wakefulness, rapid eye movement (REM) sleep, and non-REM sleep (NREM).
Anticipated Tags and Synopsis of the Film
Social tagging may lead to discovering new works of art, tales, music, facts, and feelings. Information gleaned from this study might be utilized to improve automated algorithms for film classification.
Automatic ratings give viewers an idea of what to expect from a film, while suggestion algorithms point them in the direction of similar fare. The drive of this project is to compile information on movies and film summaries.
By employing this method, we were able to create 70 tags that highlight distinct elements of film plots and analyse the multi-label interactions between these tags and more than 14,000 plot summaries.
To determine whether or not the labels make sense, the film’s genre and the characters’ arcs are examined. Finally, we’ll utilize this dataset to test whether or not we can infer tag values from plot summaries.
Our research indicates that this corpus will be helpful for future applications of story analysis.
Inadequate labelling can have a significantly harmful impact on the user experience. Predict many tags with good recall and accuracy without being severely constrained by latency.
Software-Based Forensic Image Creation
To improve or correct the photo, we employed specific editing tools. Thanks to advancements in machine learning, processing images has become much more streamlined. Image generator data may now be used to access forensic drawings created using GAN.
Researchers in computer vision, image processing, and machine learning have been keen to find ways to automate the creation and detection of facial features in visual material for some time.
Here, we employ machine learning methods and tools to produce a picture that passes off as a sketch. The method’s ability to simplify the production of forensic photographs may lead to more compelling visuals. Because of the extensive use of automation, personnel is no longer necessary.
Both the generator and discriminator in the network must be trained before they can be used.
The generator and the discriminator can be taught independently.
Learn to Spot a Credit Card Scam
Using a credit card that you know was stolen might land you in jail. The primary goals of this investigation are (1) to categorize the many types of counterfeit credit cards and (2) to contrast and contrast the various techniques used to identify fraud. Recent research on methods for identifying credit card fraud will also be discussed.
This page is helpful since it defines key terms and gives data on credit card fraud. Several processes may be developed and necessary depending on the type of fraud experienced by the credit card industry or financial institutions.
The study’s recommendations are thought to be more cost-effective than alternatives not included in it. This precaution is highlighted because of the seriousness of the problem of credit card fraud.
Even ethical issues arise when good individuals are wrongly accused of crimes like credit card fraud. Logistic regression goes by a variety of other names as well.
Conclusion
So, AI is a promising area with many applications for your projects. If you want to hone your AI skills, try your hand at these exercises. These exercises will speed up your AI education and prepare you for the workforce.
You’re welcome to contribute to exciting AI initiatives regardless of your level of expertise in the field.
Comments are closed.