- Affective Computing (Emotion in machines, emotional understanding, facial expression, self motivation): Affective computing is a branch of artificial intelligence that deals with the design of systems and devices which can recognize, interpret, and process emotions. It is an interdisciplinary field spanning computer sciences, psychology, and cognitive science. [top]
- Intelligent agents:
In computer science, an intelligent agent (IA) is a software agent that assists users and will act on their behalf, in performing non-repetitive computer-related tasks. An agent in the sense of the word is like an insurance agent or travel agent. While the working of software agents used for operator assistance or data mining (sometimes referred to as bots) is often based on fixed pre-programmed rules, "intelligent" in this context is often taken to imply the ability to adapt and learn.
In artificial intelligence, an intelligent agent is used for intelligent actors, which observe and act upon an environment, to distinguish them from intelligent thinkers isolated from the world. An agent in this sense of the word is an entity that is capable of perception and action. Such an agent might be a robot or an embedded real time software system - and is intelligent if it interacts with its environment in a manner that would normally be regarded as intelligent if that interaction were carried out by a human being. [top]
- Intelligent user interfaces:
Computer applications grow increasingly complex and through the use of artificial intelligence technology software systems begin to achieve the ability to reason and make decisions on their own. Consequently, the design of effective and efficient human-computer interfaces becomes ever more critical to overall system performance. Advanced applications are characterized by large amounts of information to be conveyed and understood, complex task structures, real-time performance characteristics, and incorporation of autonomous or semiautonomous agents. The requirements imposed by human-computer interaction with such systems exceed the capabilities of conventional interfaces which often fail to reflect the semantics of its users' tasks and problem domain properly. Intelligent user interfaces aim to cope with these serious semantic problems and help users to access information or solve complex tasks by being sensitive to a user's knowledge, misconceptions, goals, and plans. [top]
- Emotional Learning:
Emotion can have a powerful impact on memory. Numerous studies have shown that the most vivid autobiographical memories tend to be of emotional events, which are likely to be recalled more often and with more clarity and detail than neutral events.The activity of emotionally enhanced memory retention can be linked to human evolution; during early development, responsive behavior to environmental events would have progressed as a process of trial and error. Survival depended on behavioral patterns that were repeated or reinforced through life and death situations. Through evolution, this process of learning became genetically embedded in humans and all animal species in what is known as "fight or flight" instinct. Artificially inducing this instinct through traumatic physical or emotional stimuli essentially creates the same physiological condition that heightens memory retention by exiting neuro-chemical activity affecting areas of the brain responsible for encoding and recalling memory. [top]
- Image processing:
Image processing is any form of information processing for which the input is an image, such as photographs or frames of video; the output is not necessarily an image, but can be for instance a set of features of the image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it. [top]
- Computer Vision:
Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images. The image data can take many forms, such as a video sequence, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply the theories and models of computer vision to the construction of computer vision systems.
Computer vision can also be described as a complement (but not necessarily the opposite) of biological vision. In biological vision, the visual perception of humans and various animals are studied, resulting in models of how these systems operate in terms of physiological processes. Computer vision, on the other hand, studies and describes artificial vision system that are implemented in software and/or hardware. Interdisciplinary exchange between biological and computer vision has proven increasingly fruitful for both fields. Sub-domains of computer vision include scene reconstruction, event detection, tracking, object recognition, learning, indexing, ego-motion and image restoration. [top]
- Data and image fusion:
Data fusion, is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences, which will be more efficient than if they were achieved by means of a single source.
In computer vision, Multisensor Image Fusion is the process of combining relevant information from two or more images into a single image. The resulting image will be more informative than any of the input images. In remote sensing applications, the increasing availability of space borne sensors gives a motivation for different image fusion algorithms. Several situations in image processing require high spatial and high spectral resolution in a single image. Most of the available equipment is not capable of providing such data convincingly. The image fusion techniques allow the integration of different information sources. The fused image can have complementary spatial and spectral resolution characteristics. But, the standard image fusion techniques can distort the spectral information of the multispectral data, while merging. [top]
