… of the convolutional neural network algorithm, this paper proposes a … convolutional neural
network algorithm. First, a recurrent neural network is introduced into the convolutional neural …

… the Artificial Neural Network (… artificial intelligence in common machine learning tasks. One
of the most impressive forms of ANN architecture is that of the Convolutional Neural Network (…

… To construct an AI-based diagnostic system, we used a deep neural network architecture …
SSD is a deep CNN that consists of 16 layers or more. The Caffe deep learning framework, …

… on developments in artificial neural networks in which multiple network layers are added to
… behind deep convolutional neural networks (CNNs) is provided in Fig 1. Neural networks aim …

… Using these, we developed deep learning through convolutional neural networks (CNNs).
We also prepared 1118 test images for 47 patients with 49 esophageal cancers and 50 …

… The utility of artificial intelligence (AI) in colonoscopy has gained popularity in current
times. Recent trials have evaluated the efficacy of deep convolutional neural network (DCNN)-…

… a convolutional neural network particularly for breast cancer classification tasks. However, a
common problem in any artificial intelligence … using convolutional neural networks to identify …

… of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare
the performance of an AI algorithm, the lung cancer prediction convolutional neural network …

… Here, we study the applicability of deep neural network-based artificial intelligence in … We
use deep learning-based on convolutional neural network and fully convolutional network with …

… Deep Neural Networks (DNN) provide exceedingly better results in image classification
tasks compared to other techniques in Artificial Intelligence (AI), and can often surpass the …