An Odor Recognition Algorithm of Electronic Noses Based on Convolutional Spiking Neural Network for Spoiled Food Identification

TL;DR: In this paper, a review of the capabilities and prospects of TENG in cancer treatment, recovery, management, prevention and diagnosis is presented, where TENGs with artificial intelligence has been applied in precision cancer research.

TL;DR: In this article , the authors reviewed the principles and performances of typical gas recognition methods of the electronic nose up to now and compares and analyzes the classical gas recognition method and the neural network-based methods.

TL;DR: In this article , a review of the capabilities and prospects of TENG in cancer treatment, recovery, management, prevention and diagnosis is presented, where TENGs with artificial intelligence has been applied in precision cancer research.

TL;DR: This work presents a residual learning framework to ease the training of networks that are substantially deeper than those used previously, and provides comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth.

TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.

TL;DR: Scikit-learn as mentioned in this paper is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.

TL;DR: Scikit-learn as mentioned in this paper is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.