Results 41 to 50 of about 1,313 (183)

Deep Neural Networks Using Residual Fast-Slow Refined Highway and Global Atomic Spatial Attention for Action Recognition and Detection

IEEE Access, 2021
In this work, we propose two Deep Neural Networks, DNN-1 and DNN-2, based on residual Fast-Slow Refined Highway (FSRH) and Global Atomic Spatial Attention (GASA) to effectively recognize and detect actions.
Manh-Hung Ha, Oscal Tzyh-Chiang Chen
doaj   +1 more source

Non-destructive detection of single-seed viability in maize using hyperspectral imaging technology and multi-scale 3D convolutional neural network

Frontiers in Plant Science, 2023
The viability of Zea mays seed plays a critical role in determining the yield of corn. Therefore, developing a fast and non-destructive method is essential for rapid and large-scale seed viability detection and is of great significance for agriculture ...
Yaoyao Fan, Yaoyao Fan, Ting An, Qingyan Wang, Guang Yang, Wenqian Huang, Zheli Wang, Chunjiang Zhao, Chunjiang Zhao, Xi Tian   +9 more
doaj   +1 more source

BEMD-3DCNN-Based Method for COVID-19 Detection [PDF]

, 2021
Abstract Coronavirus outbreak continues to spread around the world and none knows when it will stop. Therefore, from the first day of the virus identification in Wuhan, scientists have launched numerous research projects to understand the nature of the virus, how to detect it, and search for the right medicine to help and protect patients.
Ali Riahi, Omar Elharrouss, Noor Almaadeed, Somaya Al-Maadeed   +3 more
openaire   +1 more source

Automatic Recognition of Colon and Esophagogastric Cancer with Machine Learning and Hyperspectral Imaging [PDF]

, 2023
There are approximately 1.8 million diagnoses of colorectal cancer, 1 million diagnoses of stomach cancer, and 0.6 million diagnoses of esophageal cancer each year globally.
Hostettler, Alexandre, Diana, Michele, Bencteux, Valentin, Chalopin, Claire, Barberio, Manuel, Maktabi, Marianne, Jansen-Winkeln, Boris, Marescaux, Jacques, Gockel, Ines, Collins, Toby   +9 more
core   +3 more sources

Detecting Asymptomatic Infections of Rice Bacterial Leaf Blight Using Hyperspectral Imaging and 3-Dimensional Convolutional Neural Network With Spectral Dilated Convolution

Frontiers in Plant Science, 2022
Rice is one of the most important food crops for human beings. Its total production ranks third in the grain crop output. Bacterial Leaf Blight (BLB), as one of the three major diseases of rice, occurs every year, posing a huge threat to rice production ...
Yifei Cao, Yifei Cao, Peisen Yuan, Huanliang Xu, José Fernán Martínez-Ortega, Jiarui Feng, Jiarui Feng, Zhaoyu Zhai   +7 more
doaj   +1 more source

Detecting anomalies in security cameras with 3DCNN and ConvLSTM

, 2023
Abstract This research introduces a novel deep learning-based approach for anomaly identification in surveillance films. The suggested approach is built on a deep network that has been taught to recognise objects and human activity in films. The technique was evaluated on five large-scale datasets from the real world, including UCF-Crime, XD ...
Esraa A. Mahareek, Eman K. El-Sayed, Nahed M. El-Desouky, Kamal A. El-Dahshan   +3 more
openaire   +1 more source

Comparison of model selection and data bias on the prediction performance of purpleback flying squid (Sthenoteuthis oualaniensis) fishing ground in the Northwest Indian Ocean

Ecological Indicators
Purpleback flying squid (Sthenoteuthis oualaniensis, PFS) is one of the critical economically cephalopod species in the northwest Indian Ocean, and the accurate model and dataset selection are critical parameters for predicting and managing the PFS ...
Haibin Han, Bohui Jiang, Delong Xiang, Yongchuang Shi, Siyuan Liu, Chen Shang, Xinye Zhao, Heng Zhang, Yuyan Sun   +8 more
doaj   +1 more source

MIA-3DCNN: COVID-19 Detection Based on a 3D CNN

CoRR, 2023
Early and accurate diagnosis of COVID-19 is essential to control the rapid spread of the pandemic and mitigate sequelae in the population. Current diagnostic methods, such as RT-PCR, are effective but require time to provide results and can quickly overwhelm clinics, requiring individual laboratory analysis.
Igor Kenzo Ishikawa Oshiro Nakashima, Giovanna Vendramini, Hélio Pedrini   +2 more
openaire   +3 more sources

Decoy set detail used for comparison to previous 3DCNN method based on whole protein structures.

, 2019
Decoy set detail used for comparison to previous 3DCNN method based on whole protein structures.
Rin Sato (7348736), Takashi Ishida (69157)   +1 more
core   +1 more source

Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning [PDF]

, 2023
OBJECTIVE: Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex.
Eric J. Lenze, Patrick H. Luckett, Snyder, Abraham, Abraham Z. Snyder, Park, Ki, Wetherell, Julie, John J. Lee, Luckett, Patrick, Leuthardt, Eric, Beau M. Ances, Joshua S. Shimony, Lee, John, Eric C. Leuthardt, Lisa T. Eyler, Eyler, Lisa, Ki Yun Park, Julie Loebach Wetherell, Shimony, Joshua, Ances, Beau, Lenze, Eric   +19 more
core   +1 more source