Results 21 to 30 of about 5,327,863 (254)
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
doaj +1 more source
MostafaNabieh/Convolutional-Neural-Network-CNN: CNN Project
, 2020 Cnn project by Tensorflow ...
Mostafa Nabieh, Mostafa Nabieh (8597619)
core +1 more source
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.
core +1 more source
CNN-LSTM neural network architecture.
, 2021 CNN-LSTM neural network architecture.
Hyun-Koo Kang (11307727) +5 more
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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
doaj +2 more sources
, 2023 This study presents a data-driven finite element-machine learning surrogate model for predicting the end-to-end full-field stress distribution and stress concentration around an arbitrary-shaped inclusion.
Rezasefat, Mohammad, Hogan, James D.
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Forecasting Nonadiabatic Dynamics using Hybrid Convolutional Neural Network/Long Short-Term Memory Network [PDF]
, 2021 Modeling nonadiabatic dynamics in complex molecular or condensed-phase systems has been challenging especially for the long-time dynamics. In this work, we propose a time series machine learning scheme based on the hybrid convolutional neural network ...
Jiebo, Li +3 more
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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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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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Inference time for each Convolutional Neural Network (CNN) model.
, 2022 Inference time for each Convolutional Neural Network (CNN) model.
Min-Chang Jang (12133336) +8 more
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