Learning to Detect Cracks on Damaged Concrete Surfaces Using Two-Branched Convolutional Neural Network

In this chapter, we introduce unsupervised pattern recognition using a spiking neural network (SNN) based on the proposed synapse device and neuron circuit.. Unsupervised

In this paper, the crack detection algorithm of micro-electro mechanism systems(MEMS) based grid-type sensor is comprehended for detecting micro cracks using

An RNN model is neural network architecture using a single layer or multiple layers, consisting of circulation connections, commonly applied for learning the

– An artificial neural network that fits the training examples, biased by the domain theory. Create an artificial neural network that perfectly fits the domain theory

따라서 본 절에서는 Mathworks에서 제공하는 Deep Learning Toolbox의 Artificial Neural Network(ANN: 인공 신경망) 알고리즘을 이용해 Hot Swap 동작 시 발생하는

Motivation – Learning noisy labeled data with deep neural network.

Human Actions Tracking and Recogni tion Based on Body Parts Detection via Artificial Neural Network.. ○ 인공 신경망 ->

Human Actions Tracking and Recogni tion Based on Body Parts Detection via Artificial Neural Network.. ○ 인공 신경망 ->