Best Research and Thesis in Computer Science and Engineering(Artificial Intelligence)

Deep Learning

Deep Learning is a subfield of Machine Learning that uses machine learning algorithms for data representation. Deep Learning is employed in deep neural networks, deep belief network, and recurrent neural networks and finds its application in computer vision, speech recognition, drug discovery, natural language processing, and bioinformatics. It is a hot topic for project and thesis in artificial intelligence. All the models of deep learning are based on the concept of artificial neural networks. There are algorithms designed to implement the concept of deep learning in different tasks. 

Robotics

Robotics is a branch of the field which is a mixture of mechanical, electrical, and computer science engineering and uses machine learning algorithms for designing and working with robots. Robots are replacing the manpower in industries for construction and manufacturing. The application of robotics includes military robots, agriculture robots, domestic robots etc. It is an interesting topic in artificial intelligence for research purpose. There are various components employed to create a robot. In the near future, robots will replace everything where human force is required. Robotics brings together different fields of science and technology. 

Natural Language Processing

It is a branch of artificial intelligence that deals with the way computer and human language interact with each other. The main functions of this process include speech recognition, natural language understanding, and natural language generation. Statistical language processing is also a part of this. It is the latest technology and one of the hot topics in artificial intelligence. Various search engines use Natural Language Processing deep learning models for machine translation. The working of natural language processing is based on deep learning. 

Reinforcement Learning

Reinforcement Learning is a part of Artificial Intelligence that determines how an agent should act in an environment in order to maximize its performance. There are various algorithms designed for this purpose. It is different from supervised and unsupervised learning. It is also a very good topic for thesis and research. Using reinforcement learning, a machine can learn from its behavior in the environment. Techniques like Decision Trees and Neural Networks are used to solve complex problems using reinforcement learning. 

Artificial Neural Network

Artificial Neural Network imitates the working of a human brain. The nodes represent the biological neuron. The nodes are linked with each other with a value assigned to each node known as node value. The learning strategies in artificial neural networks are supervised learning, unsupervised learning and reinforcement learning. Feed Forward and Feedback are the two types of artificial neural network Topologies. 

Expert System

Expert System is a good area for research in artificial intelligence. Expert Systems solve complex computational problems. The main components of an expert system are Knowledge Base, Inference Engine, and User Interface. The knowledge base can be Factual and Heuristic. Forward chaining is also used in expert systems.

Fuzzy Systems

Fuzzy Systems produce a definite output for an indefinite input through fuzzy logic. Fuzzy Logic is a method of reasoning resembling human reasoning. Fuzzy Logic makes decisions in the form of Yes or No. The fuzzy system architecture includes the Fuzzification module, defuzzification module, knowledge base, and the inference engine. The concept of fuzzy logic is used in the commercial and practical purposes. There are membership functions used in the fuzzy systems. 

Computer Vision

Computer Vision is a part of artificial intelligence that deals with making computers understand the digital images and videos. It is an important research and thesis area in artificial intelligence. The main tasks performed in computer vision are visualizing, acquiring, and analyzing. Useful information is extracted from the images which are analyzed later on. The main applications of computer vision are object recognition, motion sensing, image restoration, augmented reality, forensics, and pose estimation. 

Biometrics

Biometrics is a scientific authentication method used for identification and access control. It is a hot topic in artificial intelligence for thesis and research. The word biometrics is made up of two words bio means life and metrics mean to measure. Biometric systems have a lot of applications in corporate as well as public sectors to verify the identity of a person. Biometric systems are categorized on the basis of physiological characteristics and behavioral characteristics.

Computational Biology

It is a field that deals with the study of a large set of biological data with methods like analytical, mathematical, and simulation. Artificial Intelligence has played a major role in the development of computational biology. It has a number of applications especially in studying the sequence and structure of biological molecules. It is also used in genetic evolution and spatial modeling. Computational biology is a very broad field used for different type of environmental data. Different methods used in computational biology for computation include complexity theory, machine learning, and robotics.