Results 151 to 160 of about 1,313 (183)
Predicting unknown binding sites for transition metal based compounds in proteins
Levy A, Rothlisberger U.
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A hybrid approach for search and rescue using 3DCNN and PSO
Neural Computing and Applications, 2020Search and rescue are essential applications of disaster management in which people are evacuated from the disaster-prone area to a safer place. This overall process of search and rescue can be more efficient if an automated system can quickly locate the human or area where rescue is required.
Balmukund Mishra +3 more
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3DCNN for Pulmonary Nodule Segmentation and Classification
2020Lung cancer is the leading cause of cancer-related death. Early stage lung cancer detection using computed tomography (CT) could prevent patient death effectively. However, millions of CT scans will have to be analyzed thoroughly worldwide, which represents an enormous burden for radiologists. Therefore, there is significant interest in the development
Zhenhuan Tian +3 more
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3DCNN predicting brain age using diffusion tensor imaging
Medical & Biological Engineering & Computing, 2023Neuroimaging-based brain age prediction using deep learning is gaining popularity. However, few studies have attempted to leverage diffusion tensor imaging (DTI) to predict brain age. In this study, we proposed a 3D convolutional neural network model (3DCNN) and trained it on fractional anisotropy (FA) data from six publicly available datasets (n ...
Yuqi Wang +5 more
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Effective Fusion of 3DCNN and Convolutional GRU for Gesture Recognition
2020 IEEE 6th International Conference on Computer and Communications (ICCC), 2020Gesture recognition is a challenging topic in the field of computer vision. This paper combines the advantages of 3DCNN and ConvRNN in spatial and temporal feature extraction respectively and proposes a network structure of “Res3D&Dilated+ConvGRU+2DCNN”.
Luo Yangbiao, Wu Muqing, Xu Weiyao
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A View-invariant Skeleton Map with 3DCNN for Action Recognition
2019 Chinese Automation Congress (CAC), 2019Skeleton based human action recognition is a challenging task in the field of computer vision, which is easily affected by variant camera viewpoint. A novel view-invariant feature is proposed in this paper. We encode the spatial-temporal information of skeleton joint points sequences into a view-invariant skeleton map (VISM), and employ a 3D ...
Yang Zhao +4 more
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Fusion-3DCNN-max3P: A dynamic system for discovering patterns of predicted congestion
2020 IEEE International Conference on Big Data (Big Data), 2020Nowadays, resolving chaotic traffic situations, which usually link to traffic congestion, is an essential need. It poses many risks to commuters like traffic accidents, especially during bad weather situations. Besides, owing to the exponential growth of IoT technologies, it is easier than ever to collect a huge amount of urban sensing data. Therefore,
Minh-Son Dao +3 more
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Classification of 3D interpolated EEG signals using hybrid R-3DCNN
Proceedings of the 35th Annual ACM Symposium on Applied Computing, 2020Preserving both, the spatial and temporal features of electroencephalogram (EEG) signals, have been the most sought after objectives of researchers to extract better features. To maintain spatial features, each electrode of an EEG cap, located on the scalp of a subject, has to be represented such that the spatial locations of the electrodes are ...
Vedang Mandhana, Rutuja Taware
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Hand Gesture Recognition by Using 3DCNN and LSTM with Adam Optimizer
2018A two-step hand gesture recognition system is proposed to classify gestures from different subjects performed under widely varying lighting conditions. First, 3D Convolutional neural network are fine-tuned to classify each hand gesture. Then, the fine-tuned 3D Convolutional neural network are used to learn spatio-temporal features for Long short-term ...
Siyu Jiang, Yimin Chen
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