Results 21 to 30 of about 3,957 (194)

Energy-Efficient and High-Performance Ship Classification Strategy Based on Siamese Spiking Neural Network in Dual-Polarized SAR Images

Remote Sensing, 2023
Ship classification using the synthetic aperture radar (SAR) images has a significant role in remote sensing applications. Aiming at the problems of excessive model parameters numbers and high energy consumption in the traditional deep learning methods ...
Xinqiao Jiang, Hongtu Xie, Zheng Lu, Jun Hu   +3 more
doaj   +1 more source

Host-Based Intrusion Detection Model Using Siamese Network

IEEE Access, 2021
As cyberattacks become more intelligent, the difficulty increases for traditional intrusion detection systems to detect advanced attacks that deviate from previously stored patterns. To solve this problem, a deep learning-based intrusion detection system
Daekyeong Park, Sangsoo Kim, Hyukjin Kwon, Dongil Shin, Dongkyoo Shin   +4 more
doaj   +1 more source

Research on few-shot power detection of siamese network based on improved RPN

Journal of Hebei University of Science and Technology, 2023
In order to solve the problems of difficulty, low efficiency, and insufficient data to support large-scale training in existing power system detection methods, a few-shot detection method based on siamese network was proposed.
Jun FENG, Sichen PAN, Shuai ZHAO, Liangying PENG, Xiongfei FAN   +4 more
doaj   +1 more source

Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification

Journal of Cheminformatics, 2023
Siamese networks, representing a novel class of neural networks, consist of two identical subnetworks sharing weights but receiving different inputs. Here we present a similarity-based pairing method for generating compound pairs to train Siamese neural ...
Yumeng Zhang, Janosch Menke, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch, Hongtao Zhao   +6 more
doaj   +1 more source

Optimization Method for Classifier Output Repeatability Based on Siamese Networks [PDF]

Jisuanji gongcheng
In industrial surface Quality Control (QC) scenarios, deep classification neural networks are widely used to classify product images for qualified judgment or quality grading.
YU Yongtao, SUN Ao, LI Ang, ZHU Linlin
doaj   +1 more source

Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging

npj Digital Medicine, 2020
Using medical images to evaluate disease severity and change over time is a routine and important task in clinical decision making. Grading systems are often used, but are unreliable as domain experts disagree on disease severity category thresholds ...
Matthew D. Li, Ken Chang, Ben Bearce, Connie Y. Chang, Ambrose J. Huang, J. Peter Campbell, James M. Brown, Praveer Singh, Katharina V. Hoebel, Deniz Erdoğmuş, Stratis Ioannidis, William E. Palmer, Michael F. Chiang, Jayashree Kalpathy-Cramer   +13 more
doaj   +1 more source

Multiple Object Tracking via Feature Pyramid Siamese Networks

IEEE Access, 2019
When multiple object tracking (MOT) based on the tracking-by-detection paradigm is implemented, the similarity metric between the current detections and existing tracks plays an essential role. Most of the MOT schemes based on a deep neural network learn
Sangyun Lee, Euntai Kim
doaj   +1 more source

Multi-Loss Siamese Neural Network With Batch Normalization Layer for Malware Detection

IEEE Access, 2020
Malware detection is an essential task in cyber security. As the trend of malicious attacks grows, unknown malware detection with high accuracy becomes more and more challenging.
Jinting Zhu, Julian Jang-Jaccard, Paul A. Watters   +2 more
doaj   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

CNN-Siam: multimodal siamese CNN-based deep learning approach for drug‒drug interaction prediction

BMC Bioinformatics, 2023
Background Drug‒drug interactions (DDIs) are reactions between two or more drugs, i.e., possible situations that occur when two or more drugs are used simultaneously. DDIs act as an important link in both drug development and clinical treatment. Since it
Zihao Yang, Kuiyuan Tong, Shiyu Jin, Shiyan Wang, Chao Yang, Feng Jiang   +5 more
doaj   +1 more source