Results 101 to 110 of about 1,313 (183)

A Deep Learning Approach based on Two-channel 3DCNN Networks to Predict the Risk of Femoral Fracture using CT Images

Computed tomography (CT) images provide a wealth of anatomical information crucial for diagnosing femoral fractures. However, predicting these fractures poses challenges due to postural variabilities of the femur and device-related factors.
Yuan, Kaiyang, Deng, Hong-Wen, Zhao, Chen, Tang, Shaojie, Wei, Qiuyue, Zhou, Weihua, Cheng, Xiaoguang, Wang, Ling   +7 more
core   +1 more source

DDC3N: Doppler-Driven Convolutional 3D Network for Human Action Recognition

IEEE Access
In deep learning (DL)–based human action recognition (HAR), considerable strides have been undertaken. Nevertheless, the precise classification of sports athletes’ actions still needs to be completed.
Mukhiddin Toshpulatov, Wookey Lee, Suan Lee, Hoyoung Yoon, U Kang Kang   +4 more
doaj   +1 more source

Detecting anomalies in security cameras with 3D-convolutional neural network and convolutional long short-term memory [PDF]

This paper presents a novel deep learning-based approach for anomaly detection in surveillance films. A deep network that has been trained to recognize objects and human activity in movies forms the foundation of the suggested approach.
ElDesouky, Nahed M., ElSayed, Eman K., Mahareek, Esraa A., ElDahshan, Kamal A.   +3 more
core   +1 more source

A deep learning-based reconstruction model for 3D sound speed field combining underwater vertical information

Frontiers in Marine Science
IntroductionThe sound speed in the ocean significantly influences the propagation characteristics of underwater acoustic signals. Rapid acquisition of underwater three-dimensional (3D) sound speed fields is essential for target detection, acoustic ...
Hongchen Li, Yuhang Liu, Ming Li, Penghao Wang, Yuhang Zhu, Kefeng Mao, Xi Chen   +6 more
doaj   +1 more source

Learning Multiband-Temporal-Spatial EEG Representations of Emotions Using Lightweight Temporal Convolution and 3D Convolutional Neural Network

IEEE Access
Emotion recognition based on electroencephalography (EEG) has become an important topic in affective computing. However, current research does not utilize the relationship between channel frequency bands, and the trainable parameters and FLOPs of the ...
Fengjie Wu, Jiarui Liu, Jisen Yang, Lihan Zhang, Yan He, Zhaolong Lin   +5 more
doaj   +1 more source

The classification of non-standard human behavior using the proposed 3DCNN neural network

, 2022
At present, due to the rapid development of technology, there is a growing interest in the use of neural networks not only in various scientific research areas but also in several industries.
Sýkora, Peter, Vršková, Róberta, Hudec, Róbert, Kamencay, Patrik   +3 more
core  

Geospatial-based surveillance of malaria risk in Dar es Salaam using a hybrid 3DCNN + LSTM and CA model. [PDF]

Int J Health Geogr
Kanjagaile ES, Deus D, Msusa AD.
europepmc   +1 more source

Hyperspectral Fingerprints of Abdominal and Pelvic Organs. [PDF]

J Imaging
van de Weerd LS, van de Berg NJ, Rijstenberg LL, van de Laar RLO, van Beekhuizen HJ.   +4 more
europepmc   +1 more source

CholBindNet as an interpretable neural network for cholesterol-binding site classification. [PDF]

Commun Chem
Hernandez A, Bhatt A, Revilla I, Levine JE, Kosaraju SC, Luo YL.   +5 more
europepmc   +1 more source

Deep3DCCS: Geometry-Driven Collision Cross Section Prediction from Multi-View Molecular Projection Tensors. [PDF]

J Chem Inf Model
Wisanpitayakorn P, Mathema VB, Wanichthanarak K, Keawhawong T, Jariyasopit N, Saiviroonporn P, Tongdee T, Sirivatanauksorn Y, Khoomrung S.   +8 more
europepmc   +1 more source