Unit-5

Applications

Q1) What is face recognition?

A1) Face Recognition is a recognition technique used to detect faces of individuals whose images are saved in the data set. Despite the point that other methods of identification can be more accurate, face recognition has always remained a significant focus of research because of its non-meddling nature and because it is people’s facile method of personal identification.

Q2) What is object recognition?

A2) Object recognition consists of recognizing, identifying, and locating objects within a picture with a given degree of confidence.

Q3) What are the tasks in object recognition?

A3) In this process, the four main tasks are:

An important task in object recognition is to identify what is in the image and with what level of confidence. This is indicated as the probability percent in the picture below. 

                                           Figure . Classification (left) and tagging (right).

The mechanism of this task is (relatively) straightforward. It starts with the definition of the ontology, i.e. the class of objects to detect. Then, both classification and tagging identify what is in the image and the associated level of confidence. 

While classification recognizes only one class of objects, tagging can recognize multiple ones for a given image. In other words, in classification the algorithm will only remember that there is a dog, ignoring all other classes. On the other hand, in tagging, it will try to return all the best classes corresponding to the image. 

Once identified what is in the image, we want to locate the objects. There are two ways to do so: detection and segmentation.

Detection outputs a rectangle, also called bounding box, where the objects are. It is a very robust technology, prone to minor errors and imprecisions. Alternatively, segmentation identifies the objects for each pixel  in the image, resulting in a very precise map. However, the accuracy of segmentation depends on an extensive and often time-consuming training of the neural network.

Figure .  Detection (left) and segmentation (right).

If the performance of the operation is high enough, it can deliver very impressive results in use cases like cancer detection. If you want to know more, read our blog post on image recognition or cancer detection.

Q4) Explain the principle of speech recognition?

A4) Speech recognition or speech to text includes capturing and digitizing the sound waves, transformation of basic linguistic units or phonemes, constructing words from phonemes and contextually analysing the words to ensure the correct spelling of words that sounds the same.

Approach: Studying the possibility of designing a software system using one of the techniques of artificial intelligence applications neuron networks where this system is able to distinguish the sound signals and neural networks of irregular users. Fixed weights are trained on those forms first and then the system gives the output match for each of these formats and high speed.

Q5) Explain the application of robots?

A5) AI consulting services have succeeded in building robots. They are being used in the industrial sector to handle the preparation of raw materials. They are also being used to control, cut, weld, color, drill, polish, and more such activities. With the addition of artificial intelligence, the execution is more precise, accurate, and enhanced than it was ever before.

The medical community has seen some pioneering new technology with the assistance of AI chatbots. New and improved machinery with the advantages of both artificial intelligence and robotics are being made. This helps to carry out clinical tests and much more.

Al robots are the reason behind all our contemporary achievements in the department of space exploration and any future developments that are under pursue. Al robots are also being sent to the different parts of the universe, different corners of space that men can never reach.

Exploration campaigns in different parts of the world, rock climbing, visiting and determining the situation in the core of the earth. Such endeavours have seen trail-blazing results with the application of  AI services.

Q6) Explain AI in E-commerce?

A6) The internet has opened the door for revolutionizing various sectors. E-commerce sector is that of the one of them. E-commerce sectors have unlocked that of the new opportunities and the scope for retailers. Retailers also have never seen such a growth in their sales. Artificial intelligence is taking that of the E-commerce to the next level.

Q7) Explain AI in Recommendation Systems?

A7) Have you ever experienced that how E-commerce websites like that of the Amazon is constantly showing that of the products similar you just checked? Well, this is the application of that of the artificial intelligence in E-commerce. AI and machine learning algorithms can predict the behaviour of the buyer from its past searches, likings, frequently bought products. By predicting the behaviour of the user, E-commerce websites are able to recommend the products that user is highly interested in. This improves the user experience as the user no longer has to spend hours searching the product. It also helps the E-commerce websites to improve that of their sales.

Q8) Explain AI in Cybersecurity?

A8) Artificial intelligence has also improved that of the cybersecurity of the E-commerce websites. It can prevent or detect any kind of fraudulent activities. E-Commerce has to deal with a lot of transactions on that of the daily basis. Cybercriminals and hackers can hack the user account to gain unauthenticated access. This can lead to that of the exposure of the private data and the online fraud. The reputation of that of the business also gets a very big blow. To prevent this, Artificial intelligence and the machine learning algorithms are developed that can mitigate that of the chances of fraud activities over that of the website.

Q9) Explain AI in CRM?

A9) CRM

In the past, Customer Relationship Management (CRM) relied on the people to collect a huge amount of data in order to collect the data and serve the clients. But today, artificial intelligence can predict which customers are most likely to make a purchase and how can we better engage with them. Artificial intelligence applications can help in identifying the trends and plan the actions according to the latest trends. With the help of machine learning algorithms, advanced CRM can learn and improve over time.

Q10) Explain AI in sales?

A10) Artificial intelligence applications can generate and predict the accurate forecast of the E-commerce business. The study of historical data, data analytics, and latest trends can help in optimizing the resource allocation, build a healthy pipeline and analyse the team performance. The managers can get a better insight into the latest trends in sales. They can analyse the trends and can improve the sales by making strategies well before time.