7 Exciting Prospects for AI-Based Research and Development (AI)

technology

Information technology (IT), computer science engineering (CSE), and AI-based research are all terms that refer to the study and development of computer software. Those interested in a computer discipline or information technology career won’t find a more motivating resource elsewhere. This repository collects the current and historical efforts of CSE and IT majors.

As a result, it compiles a repository of cutting-edge concepts for future AI projects in computer science, IT, and software engineering. Familiarity with robot differences and similarities is helpful before delving deeper into artificial intelligence research. Maintaining a grip on these skills will be very helpful in the future.

You have found the ideal place if you are a senior in an engineering or IT program and want to find out about the 7 most promising concepts for AI projects.

1. Using computer vision for vehicle counting and identification

People move to cities to be closer to services like schools, hospitals, and their places of work. Many of the biggest cities in the world have serious traffic problems. Many things lead to traffic jams.

Because of the rise in population, the government has had to build new roads, making the current system less effective. In big cities, there are sometimes traffic jams because there aren’t enough roads to fit all the cars. When more people live in cities, there are more cars on the road.

Using public transportation is like setting up a way to identify and count each car for intelligent transportation and traffic management, for instance. Another thing that makes traffic management less effective is the lack of real-time traffic data.

2. Detection Method for Intoxicated Motorists

The World Health Organization thought that 1.3 million people died in traffic accidents worldwide in 2018. (WHO).

In 2017, 91,000 individuals perished in vehicle accidents caused by drivers too weary of paying attention, and 795 died because they were too fatigued.

Researchers have found that a driver’s energy and ability to steer both go down after about two or three hours of driving.

The risks are the same at lunchtime, early afternoon, and late at night. When someone is doing something, they may get confuse, or drowsiness.

So, the Driver Drowsiness Detection System can tell if a driver is awake, sleeping with rapid eye movement (REM), or sleeping without REM (NREM).

Read more: Common Problems in Managing Payrolls

3. Synopsis of the Film, Including Anticipated Tags

You can find new art pieces, stories, songs, facts, and feelings through social tagging. There’s a chance that this information could be used to improve algorithms for classifying movies.

Moviegoers can get a good idea of what to expect from automated ratings, and algorithms can point them in the direction of similar movies. This project aims to gather information about films and summaries of movies.

Using this method, we could make 70 tags highlighting different parts of film plots and look at how these tags and more than 14,000 plot summaries interact.

The film’s genre and how the characters change are looked at to see if the labels make sense. Lastly, we will use this dataset to test the idea that plot summaries can be used to figure out tag values.

From what we’ve learned, this corpus will also be helpful for future uses of story analysis.

Inadequate labeling hurts the user’s experience directly. a. Tag prediction with a high recall and accuracy and a reasonable latency.

4. Artificial Intelligence-Generated Forensic Images

We used special software to fix the photo and make it look better. However, machine learning techniques have greatly impacted how image processing pipelines work. Forensic drawings made with GAN can now be viewed using data from image generators.

Researchers in computer vision, image processing, and machine learning have been trying for a long time to find ways to make it easier for computers to create and find faces in images.

Methods and tools for machine learning are used to make a picture that looks a lot like a sketch. Since this method speeds up the process of making forensic images, it could lead to more convincing pictures.

5. Knowing How to Spot a Credit Card Scam

If someone steals your credit card and you use it, you might be breaking the law. The main goals of this study are to (1) classify the different kinds of fake credit cards and (2) compare and contrast the different ways to find fraud. New research on spotting credit card fraud will also discuss.

On this site, you can easily find definitions of key terms and also useful statistics about credit card fraud. Depending on the type of fraud that the credit card industry or financial institutions see, they may need to use new and different methods.

It is thought that the suggestions in this study will save money. This measure is also emphasized as a way to prevent credit card fraud.

When good people wrongly accuse, moral questions may arise. However, logistic regression goes under many different names.

6. Video Game Uses for AI

The gaming industry is another area where AI applications have become widely used. Intelligent, human-like NPCs (non-player characters) can create using AI to interact with players.

Human behavior prediction is another tool that can help game designers and testers make better games. Alien: Isolation, which came out in 2014, has AI always following the player. The “Director AI,” which continually monitors your whereabouts, and the “Alien AI,” which is drive by sensors and behaviors, are examples of artificial intelligence use in this game.

7. Marketing and AI: A Practical Exploration

Marketing makes extensive use of artificial intelligence (AI)-based applications.

Artificial intelligence (AI) lets marketers make particular and targeted ads by looking at how users behave, recognizing patterns using machine learning, etc. When good people are wrongly accused of crimes like credit card fraud, it raises even moral questions.

Chatbots that use artificial intelligence (AI), natural language processing (NLP), natural language generation (NLG), and also natural language understanding (NLU) can understand what users say and respond naturally.

Conclusion

So, there are many ways you can use AI in your work. Use these exercises to test how good you are at AI. These activities will also help you learn AI faster and prepare you for the job market.

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