Results 81 to 90 of about 5,349,001 (214)

A convolutional neural network for automatic analysis of aerial imagery [PDF]

, 2014
This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted
Amanda Hodgson, Maire, Frederic, Maire, F., Hodgson, Amanda, Luis Mejias, Frederic Maire, Hodgson, A., Mejias, Luis, Mejias, L.   +8 more
core   +1 more source

Convolutional Neural Network-Based Deep Learning Approach for Automatic Flood Mapping Using NovaSAR-1 and Sentinel-1 Data [PDF]

, 2023
The accuracy of most SAR-based flood classification and segmentation derived from semi-automated algorithms is often limited due to complicated radar backscatter.
Kithsiri Perera, Apan, Armando, Andrew, Ogbaje, Armando Apan, Ogbaje Andrew, Perera, Kithsiri, Dev Raj Paudyal, Paudyal, Dev Raj   +7 more
core   +1 more source

Forest fire image recognition based on convolutional neural network

Journal of Algorithms & Computational Technology, 2019
In order to detect fire automatically, a forest fire image recognition method based on convolutional neural networks is proposed in this paper. There are two main types of fire recognition algorithms.
Yuanbin Wang, Langfei Dang, Jieying Ren
doaj   +1 more source

An Introduction to Convolutional Neural Networks

CoRR, 2015
10 pages, 5 ...
Keiron O'Shea, Ryan Nash
openaire   +3 more sources

A low-cost neural sorting network with O(1) time complexity [PDF]

, 2011
[[abstract]]In this paper, we present an O(1) time neural network with O(n1 + var epsilon) neurons and links to sort n data, var epsilon > 0. For large-size problems, it is desirable to have low-cost hardware solutions.
Lin, Shun-Shii;Hsu, Shen-Hsuan
core  

Development and Application of Convolutional Neural Network Model

Jisuanji kexue yu tansuo, 2021
Deep learning is the latest trend of machine learning and artificial intelligence research. As a new field of rapid development in the past ten years, more and more researchers pay attention to it.
YAN Chunman ,WANG Cheng
doaj   +1 more source

Doubly Convolutional Neural Networks

CoRR, 2016
Building large models with parameter sharing accounts for most of the success of deep convolutional neural networks (CNNs). In this paper, we propose doubly convolutional neural networks (DCNNs), which significantly improve the performance of CNNs by further exploring this idea.
Shuangfei Zhai, Yu Cheng 0001, Weining Lu, Zhongfei Zhang   +3 more
openaire   +4 more sources

Deep Learning and Music Adversaries [PDF]

, 2015
OA Monitor ExerciseOA Monitor ExerciseAn {\em adversary} is essentially an algorithm intent on making a classification system perform in some particular way given an input, e.g., increase the probability of a false negative.
STURM, BLT, Kereliuk, C, Kereliuk, Corey Mose, Sturm, Bob L., Larsen, Jan, Larsen, J   +5 more
core   +1 more source

Convolutional neural network structure.

, 2020
Convolutional neural network structure.
Lerui Chen (8399430), Zerui Zhang (736858), Jianfu Cao (8399433)   +2 more
core   +2 more sources

A classification method of underwater target radiated noise signals based on enhanced images and convolutional neural networks

Frontiers in Physics
As the economy and society continue to develop, the range of underwater vehicles is expanding and technology is constantly being upgraded. Consequently, it is becoming increasingly difficult to classify and identify them, and the traditional ...
Yuan Muye, Lei Zhufeng, Dang Yinuo, Shi Zanrong   +3 more
doaj   +1 more source