… to process large datasets and realize the classification and … deep learning algorithms in
the artificial intelligence (AI) field, will greatly enhance the VOC molecular recognition capability …

… Recently, Baidu’s Deep Learning Lab entered its own artificial intelligence robot in a contest
against human competitors. See: “Chinese AI team plans to challenge Google's AlphaGo: …

… processes that provide higher device performance with reduced feature sizes. These … is
realized based on TSOM combined with a deep learning model. Unlike the traditional IBO method…

… learning and deep learning. This approach uses deep learning to extract features and then
… achieving an accuracy of 88.72%. The coincidence rate between the results of the algo- …

… components are used to construct optical neural networks, thereby directly achieving
complex functions… , characteristics, and system-architecture features of the two major types …

… -object control system based on deep learning. The system will … on dry solid interfaces are
realized by integrating the control … facilitates the expansion of functions in different application …

… Abstract:In recent years, microelectronics technology has entered the era of nanoelectronics/…
technical approaches for the realization of microsystems. Deep learning technology based …

… method based on deep learning and edge computing tech⁃ nique is proposed. First of all,based
on ResNet,a deep learning model GarbageCNet is designed to realize image-… device …

… Convolutional neural networks (CNNs) stand as pivotal instruments within the realm of deep
learning, wielding their influence across an array of domains spanning from computer vision …

… Running AI algorithms represented by deep learning places great demands on computational
power of hardware. However, with Moore's Law approaching physical limitations, the …