Researchers from the University of Sciences of Tokyo (TUS) have reached an important step in terms of artificial intelligence, revealing A self-fueled artificial synapsewhich imitates the remarkable capacity of the human eye to recognize color with exceptional precision. This innovation could transform industrial vision through a wide range of real world applications – from improving autonomous vehicles to improve advanced medical diagnostics.
The study introduces a neuromorphic device capable of distinguishing colors through the visible spectrum with a resolution of 10 nanometers, a level of discrimination closely approaching that of human vision. What really distinguishes this breakthrough is its inherent energy independence: synapse generates its own electricity through integrated solar cells sensitized to coloring. This self-feeding capacity eliminates the need for large external food, a critical limitation which has historically hampered the general deployment of industrial vision systems in compact-based devices such as drones, smartphones and clothing.
Directed by Professor Associate Takashi Ikuno, the research team has designed their device by integrating two distinct types of solar cells sensitized to the coloring, each designed to respond differently to specific light wavelengths. This innovative double -cell configuration provides not only the power necessary for synapse, but also allows it to perform complex logical operations – tasks which generally require several conventional electronic components – in a single highly compact device.
Dr. Ikuno emphasizes the deep potential of this new generation optorelectronic device to develop low -power AI systems that require both high -resolution color discrimination and effective logical treatment.
To demonstrate its real viability, the team tested the synapse in a computer framework of the physical reservoir. The system has successfully recognized 18 different combinations of movements and colors (red, green and blue) with an impressive precision of 82%. Above all, this was done using a single device, a significant improvement compared to conventional systems that would require several photododids for similar tasks.
This technology is about to improve computer vision in several sectors. In the automotive industry, it could improve real -time recognition of traffic lights, traffic signs and pedestrians in autonomous vehicles, while consuming minimum power. For consumer electronics, it promises the development of more intelligent and smarter augmented / virtual reality headsets (AR / VR), portable devices and mobile devices, considerably improving battery life without compromising advanced visual recognition capacities.
In health care, where precise effectiveness and detection are essential, this technology is a particular promise. Self-fueled visual sensors could be integrated transparently into compact diagnostic tools, facilitating real-time monitoring of vital signs, such as oxygen saturation or skin conditions, without the constant need for battery recharge.
This progression aligns closely with the work of Qudata. Our team develops A wide range of computer vision solutions adapted to real needs. The expertise of Qudata extends over various applications, including Precision Healthcare.
One of our remarkable contributions lies in the field of medical imaging and radiology. Here, our team uses an advanced visual analysis based on AI to support the Early breast cancer detection. By forming the model to identify subtle models and anomalies in complex medical analyzes, such as mammograms, QUDATA technology allows health professionals to detect cancer in its first stages, when treatment is most effective and patient results are considerably improved. The Qudata solution goes beyond simple detection, often helping classification and analysis, thus improving the accuracy and efficiency of the diagnosis in radiology services.
With devices that operate independently and process complex visual data with almost human efficiency, advanced diagnoses could become more accessible and reliable for a larger world population, fundamentally transforming health care provision.
