Results 21 to 30 of about 102,675 (264)
Convolutional Neural Network (CNN): A comprehensive overview
International Journal of Multidisciplinary Research and Growth Evaluation, 2022 Convolutional neural network (CNN), a class of artificial neural network (ANN) is attracting interests of researchers in all research domain. CNN was invented for computer vision. They have also shown to be useful for semantic parsing, sentence modeling and other natural language processing related tasks. Here in this paper we discuss the basics of CNN
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Metals, 2022 Controlled cooling technology is widely used in hot-rolled steel plate production lines. The final cooling temperature directly affects the microstructure and properties of steel plates, but cooling and heat transfer constitutes a nonlinear process ...
Xiao Hu +3 more
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Information, 2018 Identification of the malignancy of tissues from Histopathological images has always been an issue of concern to doctors and radiologists. This task is time-consuming, tedious and moreover very challenging.
Abdullah-Al Nahid, Yinan Kong
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Understanding of Convolutional Neural Network (CNN): A Review
International Journal of Robotics and Control Systems, 2023 The application of deep learning technology has increased rapidly in recent years. Technologies in deep learning increasingly emulate natural human abilities, such as knowledge learning, problem-solving, and decision-making. In general, deep learning can carry out self-training without repetitive programming by humans.
Purwono Purwono +5 more
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A-CNN: Annularly Convolutional Neural Networks on Point Clouds [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Analyzing the geometric and semantic properties of 3D point clouds through the deep networks is still challenging due to the irregularity and sparsity of samplings of their geometric structures. This paper presents a new method to define and compute convolution directly on 3D point clouds by the proposed annular convolution.
Artem Komarichev +2 more
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Short-Term Load Forecasting Model of Electric Vehicle Charging Load Based on MCCNN-TCN
Energies, 2022 The large fluctuations in charging loads of electric vehicles (EVs) make short-term forecasting challenging. In order to improve the short-term load forecasting performance of EV charging load, a corresponding model-based multi-channel convolutional ...
Jiaan Zhang, Chenyu Liu, Leijiao Ge
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Effect of neural network structure in accelerating performance and accuracy of a convolutional neural network with GPU/TPU for image analytics [PDF]
PeerJ Computer Science, 2022 Background In deep learning the most significant breakthrough in the field of image recognition, object detection language processing was done by Convolutional Neural Network (CNN).
Aswathy Ravikumar +4 more
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Deep Learning: Basics and Convolutional Neural Networks (CNNs)
, 2023 Abstract Deep learning belongs to the broader family of machine learning methods and currently provides state-of-the-art performance in a variety of fields, including medical applications. Deep learning architectures can be categorized into different groups depending on their components. However, most of them share similar modules and
Vakalopoulou, Maria +4 more
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Jurnal Saintekom, 2023 The increased use of laptops and smartphones during the COVID-19 pandemic has led to an increase in the number of people suffering from nearsightedness. Convolutional Neural Network (CNN) is a class of deep learning that is capable of recognizing images ...
Pramadika Egamo, Arief Hermawan
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Case Studies on Neural Networks for Recognition in Biometric Identity Problem [PDF]
International Journal Bioautomation, 2021 Hand-dorsa vein recognition using a convolutional neural network is presented. Our network contains five convolutional layers and three full connected layers, which have high recognition and more robust.
Zhengwen Shen +3 more
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