In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition, speech recognition and natural language processing …
S Sakib, N Ahmed, AJ Kabir, H Ahmed - 2019 - preprints.org
With the increase of the Artificial Neural Network (ANN), machine learning has taken a forceful twist in recent times. One of the most spectacular kinds of ANN design is the …
Convolutional Networks Page 1 Convolutional Networks Lecture slides for Chapter 9 of Deep Learning Ian Goodfellow 2016-09-12 Adapted by mn for CMPS 392 Page 2 (Goodfellow 2016) …
X Zhao, L Wang, Y Zhang, X Han, M Deveci… - Artificial Intelligence …, 2024 - Springer
In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super …
Convolutional neural network (or CNN) is a special type of multilayer neural network or deep learning architecture inspired by the visual system of living beings. The CNN is very much …
Convolution Neural Networks, known as ConvNets exceptionally perform well in many complex machine learning tasks. The architecture of ConvNets demands the huge and rich …
J Wu - National Key Lab for Novel Software Technology …, 2017 - cs.nju.edu.cn
This is a note that describes how a Convolutional Neural Network (CNN) operates from a mathematical perspective. This note is self-contained, and the focus is to make it …
S Saha - Towards data science, 2018 - ise.ncsu.edu
The agenda for this field is to enable machines to view the world as humans do, perceive it in a similar manner and even use the knowledge for a multitude of tasks such as Image & …
Convolutional neural networks (CNNs) are one of the main types of neural networks used for image recognition and classification. CNNs have several uses, some of which are object …