Neural networks have emerged as a pivotal technology in enhancing the precision and reliability of depth of anaesthesia (DoA) monitoring. By integrating advanced signal processing techniques with ...

Transformer Architectures Transforming Visual Processing Historically, convolutional neural networks (CNNs) dominated computer vision by leveraging local spatial filters. However, transformer ...

With neural networks, computers can distinguish and recognise images similar to humans. Some of the underlying applications include facial recognition, self-driving cars, and content moderation.

New types of computing architecture, which emulate the working principles of biological neural networks, hold the promise of faster, more energy-efficient data processing.

Designed to mimic the brain itself, artificial neural networks use mathematical equations to identify and predict patterns in datasets and images.

AI’s revolution lies in the integration of automation, big data, computer vision and deep learning, forming the essential ABCD pillars that are reshaping lives.

(a) Schematic diagram of a biological neural network and (b) circuit schematic of an artificial neural network implemented in hardware using an artificial neuromorphic device. (c) Experimental ...

In the study, "A synthetic protein-level neural network in mammalian cells," published in Science, researchers showed that perceptein circuits could distinguish signal inputs with tunable decision ...

The idea of thinking machines (Turing, 1950) and the term “artificial intelligence” were introduced in the 1950s (McCarthy, 2007). The 1960s and 1970s saw the development of neural networks. The 1980s ...