Results 11 to 20 of about 149,198 (222)

Forecast Model of TV Show Rating Based on Convolutional Neural Network

open access: yesComplexity, 2021
The TV show rating analysis and prediction system can collect and transmit information more quickly and quickly upload the information to the database. The convolutional neural network is a multilayer neural network structure that simulates the operating
Lingfeng Wang
doaj   +1 more source

Speech Command Recognition using Artificial Neural Networks

open access: yesJOIV: International Journal on Informatics Visualization, 2020
Speech is one of the most effective way for human and machine to interact. This project aims to build Speech Command Recognition System that is capable of predicting the predefined speech commands. Dataset provided by Google’s TensorFlow and AIY teams is
Sushan Poudel, Dr. R Anuradha
doaj   +1 more source

A noise robust convolutional neural network for image classification

open access: yesResults in Engineering, 2021
Convolutional Neural Networks (CNNs) are extensively used for image classification. Noisy images reduce the classification performance of convolutional neural networks and increase the training time of the networks.
Mohammad Momeny   +4 more
doaj   +1 more source

Compressed CNN Plant Leaf Recognition Model Fused with Bayesian

open access: yesJournal of Harbin University of Science and Technology, 2021
Aiming at the problem that there are many parameters in the process of plant leaf recognition and it is easy to produce over-fitting,in order to reduce the cost of storage and calculation,this paper proposes a plant leaf recognition convolutional ...
YAN Ming, ZHU Liang-kuan, JING Wei-peng
doaj   +1 more source

Parallel accelerator design for convolutional neural networks based on FPGA

open access: yesDianzi Jishu Yingyong, 2021
In recent years, convolutional neural network plays an increasingly important role in many fields. However, power consumption and speed are the main factors limiting its application.
Wang Ting, Chen Binyue, Zhang Fuhai
doaj   +1 more source

Offline Handwritten Chinese Character Recognition Based on DBN and CNN Fusion Model

open access: yesJournal of Harbin University of Science and Technology, 2020
Aiming at the problem that some offline handwritten Chinese characters are similar in shape and it is difficult to extract the feature of characters and the recognition is not accurate, a convolutional neural network and deep belief network fusion model ...
LI Lanying, ZHOU Zhigang, CHEN Deyun
doaj   +1 more source

Convolutional Neural Networks

open access: yesWorks of Georgian Technical University, 2020
It is safe to say that one of the most powerful supervised deep learning models is convolutional neural networks (abbreviated as CNN or ConvNet). CNN is a class of deep learning networks, mostly applied to image data. However, CNN structures can be used in a variety of real-world problems including, but not limited to, image recognition, natural ...
Archil Prangishvili   +2 more
  +6 more sources

Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization Patterns

open access: yesBiomolecules, 2021
Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful method to
Kaisa Liimatainen   +3 more
doaj   +1 more source

Klasifikasi Teks Hadis Bukhari Terjemahan Indonesia Menggunakan Recurrent Convolutional Neural Network (CRNN)

open access: yesJurnal Teknologi Informasi dan Ilmu Komputer, 2021
Hadis merupakan sumber hukum dan pedoman kedua bagi umat Islam setelah Al-Qur’an dan banyak sekali hadis yang telah diriwayatkan oleh para ahli hadis selama ini.
Muhammad Yuslan Abu Bakar   +1 more
doaj   +1 more source

Airborne Network Traffic Identification Method under Small Training Samples

open access: yesXibei Gongye Daxue Xuebao, 2020
Due to the high cost and difficulty of traffic data set acquisition and the high time sensitivity of traffic distribution, the machine learning-based traffic identification method is difficult to be applied in airborne network environment. Aiming at this

doaj   +1 more source

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