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ROBIONICS

ROBIONICS is a company working at the cutting edge of IT technologies within specific aspects of Software Engineering specializing in Intelligent Adaptive systems incorporating Machine Learning techniques. Machine Learning and Software Development: On application of AI & SE, some of our successful AI techniques applied include knowledge-based approach, automated reasoning, expert systems, heuristic search strategies, temporal logic, planning, and pattern recognition. Thus by utilizing fuzzy sets, neural networks, genetic algorithms, genetic programming and rough sets (or any combinations) we can tackle your software development issues. ML&SE and CI&SE (computational Intelligence & software Engineering) share two common grounds: targeted software development problems, and some common techniques. By applying ML to solve your real-world problems, as a guideline, our course of actions would be Problem Formulation, Problem representation, Domain theory preparation, Performing the learning process, Analyzing and evaluating learned knowledge and Fielding the knowledge base. ML for Robotics and Automation: We aim to build systems that are truly flexible by making them able to learn and adapt to partially, known or dynamic environments, to teach themselves new tasks, and to compensate for sensor and effector defects. simulation systems: Building advanced simulation systems to help you visualize, test and achieve your ideal solutions and by putting in place specific optimization techniques to work along with your systemís processes to ensure your satisfaction with the results. vision: By application of ML, we offer effective methods for your vision systems for automating the model/concept acquisition and updating processes, adapting task parameters and representations, and using experience for generating, verifying, and modifying hypotheses as well as other computer vision ML application such as segmentation and feature extraction; learning rules, relations, features, discriminant functions, and evaluation strategies; learning and refining visual models; indexing and recognition strategies; integration of vision modules and task-level learning; learning shape representation and surface reconstruction strategies; self-organizing algorithms for pattern learning; biologically motivated modeling of vision systems that learn; and parameter adaptation, and self-calibration of vision systems. DSS systems: We aim to support you in your business and its processes by designing for you highly interactive comprehensive DSS systems thus helping the decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify, solve problems, make sense, understand and analyse what is required so that the desirable control could reach almost perfection. Machine Learning in Bioinformatics: The exponential growth of the amount of biological data available raises two problems: on one hand, efficient information storage and management and, on the other, the extraction of useful information from these data. The second problem is one of the main challenges in computational biology, which requires the development of tools and methods capable of transforming all these heterogeneous data into biological knowledge about the underlying mechanism. By Application of these tools and methods for you, it would allow you to go beyond a mere description of the data and provide knowledge in the form of testable models. By this simplifying abstraction that constitutes a model, we will be able to obtain predictions of your system.

ROBIONICS
17 Nursery Walk
Cambridge
Cambridgeshire
CB43PR
Tel: 01223307738

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Software Development Machine Learning Automation Bioinformatics vision

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ROBIONICS are listed in; Software Development Listings : Software Development Directory : Software Development in Cambridgeshire : Software Development in Cambridge : Cambridgeshire Business Directory : Cambridge Business Directory

ROBIONICS Cambridge Cambridgeshire Software Development

ROBIONICS is a company working at the cutting edge of IT technologies within specific aspects of Software Engineering specializing in Intelligent Adaptive systems incorporating Machine Learning techniques. Machine Learning and Software Development: On application of AI & SE, some of our successful AI techniques applied include knowledge-based approach, automated reasoning, expert systems, heuristic search strategies, temporal logic, planning, and pattern recognition. Thus by utilizing fuzzy sets, neural networks, genetic algorithms, genetic programming and rough sets (or any combinations) we can tackle your software development issues. ML&SE and CI&SE (computational Intelligence & software Engineering) share two common grounds: targeted software development problems, and some common techniques. By applying ML to solve your real-world problems, as a guideline, our course of actions would be Problem Formulation, Problem representation, Domain theory preparation, Performing the learning process, Analyzing and evaluating learned knowledge and Fielding the knowledge base. ML for Robotics and Automation: We aim to build systems that are truly flexible by making them able to learn and adapt to partially, known or dynamic environments, to teach themselves new tasks, and to compensate for sensor and effector defects. simulation systems: Building advanced simulation systems to help you visualize, test and achieve your ideal solutions and by putting in place specific optimization techniques to work along with your systemís processes to ensure your satisfaction with the results. vision: By application of ML, we offer effective methods for your vision systems for automating the model/concept acquisition and updating processes, adapting task parameters and representations, and using experience for generating, verifying, and modifying hypotheses as well as other computer vision ML application such as segmentation and feature extraction; learning rules, relations, features, discriminant functions, and evaluation strategies; learning and refining visual models; indexing and recognition strategies; integration of vision modules and task-level learning; learning shape representation and surface reconstruction strategies; self-organizing algorithms for pattern learning; biologically motivated modeling of vision systems that learn; and parameter adaptation, and self-calibration of vision systems. DSS systems: We aim to support you in your business and its processes by designing for you highly interactive comprehensive DSS systems thus helping the decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify, solve problems, make sense, understand and analyse what is required so that the desirable control could reach almost perfection. Machine Learning in Bioinformatics: The exponential growth of the amount of biological data available raises two problems: on one hand, efficient information storage and management and, on the other, the extraction of useful information from these data. The second problem is one of the main challenges in computational biology, which requires the development of tools and methods capable of transforming all these heterogeneous data into biological knowledge about the underlying mechanism. By Application of these tools and methods for you, it would allow you to go beyond a mere description of the data and provide knowledge in the form of testable models. By this simplifying abstraction that constitutes a model, we will be able to obtain predictions of your system.