Neural Vision System

Neurovisual System Researchers at Houston University in Texas have developed a neurovisual system that adapts the robot to a changing world. This machine is designed to explore, experience (good or bad), and make future decisions based on experience. If the rules learned through experience are no longer applicable, its ability to "learn new skills" is unusual. In simulation and hardware experiments, robots are proven to recognize objects correctly even if the values ​​related to robots change over time.

Neuromorphic engineering is an interdisciplinary field that designs artificial nerve systems such as vision system, head eye system, auditory processor, autonomous robot, etc., which is inspired from biology, physics, mathematics, computer science and electrical engineering is. The principle of physical structure and design is based on the principle of biological nervous system. In early 2006, researchers at the Georgia Institute of Technology announced field programmable neural arrays. This chip is the first of increasingly complex arrays of floating gate transistors allowing charge programmability on MOSFET gates to simulate the channel ion properties of neurons in the brain, It is the first case. One of the neurons

As a novice in NN, Mordvintsev uses a system trained to self-learn this field, absorb important papers, and identify specific objects. His curiosity is inspired by the long-standing mystery of learning deeply with neural networks. Why are their works so wonderful and what is happening in their minds? Others are asking the same question using the so-called convolution neural network (ConvNet) to detect the visual recognition system at various points in the process. ConvNets is a special form commonly used for visual recognition and not only uses a neuron-based learning system but also in biological metaphor in the same way that the receiver is placed in the visual cortex Use it. By observing these images, researchers can better understand the role of the neural network at that time.

The convolution nervous system is now used around the world. The nervous system is inspired by the human brain and is derived from the human brain. When used for image processing, it provides a human-like vision to the computer. For this reason, almost all face detection software uses a convolution neural network to improve accuracy. Even if the smartphone is using it for face detection, there are few resources to use. Manuj Aggarwal is an entrepreneur, investor, and technology enthusiast who loves start-ups, business ideas, and high-tech products. He likes tackling difficult problems and he is satisfied with advanced technology. In his 20-year career, he has been a business owner, technical architect, CTO, coder, entrepreneur consultant and so on. Manuj consulting service and details of course at tetranoodle.com