Department of Applied Pattern Recognition Systems

2) Within the framework of international grants from ISTC and USTC, the department developed a highly efficient robotic system for selective tea harvesting (see image). The process of hardware implementation of its working model is ongoing. Currently, one group in the department is developing a hybrid intelligent system to solve real-time computational intelligence procedures. This is an inductive reasoning processor that enables near-instantaneous and parallel comparison of multidimensional input vectors with all vectors in the so-called “knowledge base,” calculating comparison results as specific metrics. These metrics can be considered “similarity measures” between the current environmental state description and all descriptions stored in the processor’s memory. The operation of determining the “similarity measure” forms the basis of inductive logic. Through it, meta-procedures for artificial intelligence, such as clustering of description spaces, concept formation, insight, pattern recognition, and more, can be developed. The well-developed elemental base of modern optoelectronics and optoelectronic devices with coordinate addressing enables the hardware implementation of the inductive reasoning processor. Combining and integrating various reasoning systems into a unified hybrid system represents a highly promising research area, offering opportunities for the development of next-generation intelligent systems.