Results 21 to 30 of about 5,349,001 (214)
Speech Command Recognition using Artificial Neural Networks
JOIV: 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
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A noise robust convolutional neural network for image classification
Results 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
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Artificial Neural Networks and Evolutionary Computation in Remote Sensing [PDF]
, 2021 Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images.
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Hyperbolic Convolutional Neural Networks
CoRR, 2023 Deep Learning is mostly responsible for the surge of interest in Artificial Intelligence in the last decade. So far, deep learning researchers have been particularly successful in the domain of image processing, where Convolutional Neural Networks are used.
Andrii Skliar, Maurice Weiler
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Convolutional neural network aided chemical species tomography for dynamic temperature imaging [PDF]
, 2022 Chemical Species Tomography (CST) using Tunable Diode Laser Absorption Spectroscopy (TDLAS) is an in-situ technique to reconstruct the two-dimensional temperature distributions in combustion diagnosis.
Lengden, Michael +5 more
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Compressed CNN Plant Leaf Ｒecognition Model Fused with Bayesian
Journal 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
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Simplicial Convolutional Neural Networks
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 Graphs can model networked data by representing them as nodes and their pairwise relationships as edges. Recently, signal processing and neural networks have been extended to process and learn from data on graphs, with achievements in tasks like graph signal reconstruction, graph or node classifications, and link prediction.
Maosheng Yang, Elvin Isufi, Geert Leus
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Orthogonal Convolutional Neural Networks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Deep convolutional neural networks are hindered by training instability and feature redundancy towards further performance improvement. A promising solution is to impose orthogonality on convolutional filters. We develop an efficient approach to impose filter orthogonality on a convolutional layer based on the doubly block-Toeplitz matrix ...
Jiayun Wang +3 more
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Offline Handwritten Chinese Character Recognition Based on DBN and CNN Fusion Model
Journal 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
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Parallel accelerator design for convolutional neural networks based on FPGA
Dianzi 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
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