Post by account_disabled on Feb 25, 2024 6:40:13 GMT
The start date of the Summer STEM Academy is approaching: full immersion in STEM disciplines (Science, Technology, Engineering, Mathematics) officially begins on August 31st for deserving students selected throughout Italy. This year we will also participate in the ambitious event organized by the Alumni Association of the Galilean School of Higher Studies, in collaboration with the Galilean School of Higher Studies and the Alumni Association of the University of Padua . Our Chief Operation Officer, Dr. Tommaso De Marchi, will talk about neural networks and image recognition: the theory will be accompanied by a practical laboratory in which students will be able to try their hand at various activities thanks to a dedicated platform: an educational and stimulating experience! If thanks to the interview with Tommaso , we were able to get to know him better and provide a general overview of his lessons, in this article we want to delve deeper into the topic of artificial intelligence: neural networks and image recognition are, in fact, the true heart of the lessons that Tommaso will hold remotely for the children of the Summer STEM Academy.
Artificial intelligence: neural networks and image recognition Artificial intelligence is a branch Chinese Student Phone Number List of computer science that aims to develop algorithms to operate cognitively, just as the human brain does. In essence, an artificial intelligence system must: Memorize knowledge; Apply knowledge to solve problems; Gain new knowledge through experience. This is where artificial neural networks come into play: processing systems inspired by the nervous systems of living beings. The single neuron receives signals from the input links, calculates a result and sends it to the output links. What does a neural network do? The data entered becomes points in a space of N dimensions and the neural network tries to define the function that identifies the data entered in the best way.
Summer STEM Academy: neural networks and image recognition to promote artificial intelligence Network training is a fundamental issue for image recognition: in fact, most networks learn from their errors by updating the weights of the inputs in the neurons. Tom Mitchell in 1997 in his book Machine Learning , defined the concept of machine learning: “a program learns from experience (E) with respect to a class of problems (T) and a performance measure (P). If his performance on the problems in (T), as measured by (P), improves with experiences in (E), then it is called machine learning.” Image recognition detects and identifies an object or detail in a digital image. What are the steps of image recognition? Image acquisition; Pre-processing via noise reduction and isolation of known patterns from the background; Details extraction; Neural network training and application.
Artificial intelligence: neural networks and image recognition Artificial intelligence is a branch Chinese Student Phone Number List of computer science that aims to develop algorithms to operate cognitively, just as the human brain does. In essence, an artificial intelligence system must: Memorize knowledge; Apply knowledge to solve problems; Gain new knowledge through experience. This is where artificial neural networks come into play: processing systems inspired by the nervous systems of living beings. The single neuron receives signals from the input links, calculates a result and sends it to the output links. What does a neural network do? The data entered becomes points in a space of N dimensions and the neural network tries to define the function that identifies the data entered in the best way.
Summer STEM Academy: neural networks and image recognition to promote artificial intelligence Network training is a fundamental issue for image recognition: in fact, most networks learn from their errors by updating the weights of the inputs in the neurons. Tom Mitchell in 1997 in his book Machine Learning , defined the concept of machine learning: “a program learns from experience (E) with respect to a class of problems (T) and a performance measure (P). If his performance on the problems in (T), as measured by (P), improves with experiences in (E), then it is called machine learning.” Image recognition detects and identifies an object or detail in a digital image. What are the steps of image recognition? Image acquisition; Pre-processing via noise reduction and isolation of known patterns from the background; Details extraction; Neural network training and application.