Results 111 to 120 of about 5,528,069 (258)
Advanced Science, EarlyView.Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Deep Convolutional Neural Network for Melanoma Detection using Dermoscopy Images
, 2020 Deep Convolutional Neural Network for Melanoma Detection using Dermoscopy ...
Roopak Sinha (17900219) +2 more
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Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Application of deep learning for division of petroleum reservoirs
MATEC Web of Conferences, 2018 Traditional methods of dividing petroleum reservoirs are inefficient, and the accuracy of onehidden-layer BP neural network is not ideal when applied to dividing reservoirs.
Qin Yaqiong, Ye Zhaohui, Zhang Conghui
doaj +1 more source
Advanced Science, EarlyView.By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
Crowd Density Estimation Using Deep Learning: A Convolutional Neural Network Approach for Real-time Monitoring [PDF]
Crowd density estimation is an essential aspect of public safety, urban management, and event monitoring. The emergence of deep learning techniques has revolutionized this domain by providing scalable, efficient, and accurate methods for estimating crowd
Jagriti, Singh, Khushi, Kawade
core
Correlation of the QTc model and the Deep Neural Network (Deep Convolutional Network).
, 2018 Correlation of the QTc model and the Deep Neural Network (Deep Convolutional Network).
Zachi I. Attia (5675246) +6 more
core +1 more source
Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks
Advanced Science, EarlyView.A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu +5 more
wiley +1 more source
Spectral convolutional neural network for music classification
, 2015 Our system submitted to the MIREX 2015 music/speech classification and detection as well as the audio classification tasks for genre and mood recognition comprises a Convolutional Neural Network approach adapted to psycho-acoustically motivated ...
Lidy, Thomas
core +2 more sources
康复学报ObjectiveTo evaluate the decoding accuracy and model performance of a graph spatio-temporal convolutional neural network (G-STCNN) in motor intention recognition of stroke patients.MethodsWe developed a novel G-STCNN model by integrating graph ...
XU Hui +5 more
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