Advancements in Image Recognition: A Siamese Network Approach
Journal Title: Information Dynamics and Applications - Year 2024, Vol 3, Issue 2
Abstract
In the realm of computer vision, image recognition serves as a pivotal task with extensive applications in intelligent security, autonomous driving, and robotics. Traditional methodologies for image recognition often grapple with computational inefficiencies and diminished accuracy in complex scenarios and extensive datasets. To address these challenges, an algorithm utilizing a siamese network architecture has been developed. This architecture leverages dual interconnected neural network submodules for the efficient extraction and comparison of image features. The effectiveness of this siamese network-based algorithm is demonstrated through its application to various benchmark datasets, where it consistently outperforms conventional approaches in terms of accuracy and processing speed. By employing weight-sharing techniques and optimizing neural network pathways, the proposed algorithm enhances the robustness and efficiency of image recognition tasks. The advancements presented in this study not only contribute to the theoretical understanding but also offer practical solutions, underscoring the significant potential and applicability of siamese networks in advancing image recognition technologies.
Authors and Affiliations
Jiaqi Du, Wanshu Fu, Yi Zhang, Ziqi Wang
Keywords
Related Articles
- EP ID EP744288
- DOI https://doi.org/10.56578/ida030202
- Views 10
- Downloads 1
A Comparative Review of Internet of Things Model Workload Distribution Techniques in Fog Computing Networks
In the realm of fog computing (FC), a vast array of intelligent devices collaborates within an intricate network, a synergy that, while promising, has not been without its challenges. These challenges, including data los...
Enhancing Pneumonia Diagnosis with Transfer Learning: A Deep Learning Approach
The significant impact of pneumonia on public health, particularly among vulnerable populations, underscores the critical need for early detection and treatment. This research leverages the National Institutes of Health...
A Deep Convolutional Neural Network Framework for Enhancing Brain Tumor Diagnosis on MRI Scans
Brain tumors are a critical public health concern, often resulting in limited life expectancy for patients. Accurate diagnosis of brain tumors is crucial to develop effective treatment strategies and improve patients' qu...
A Comprehensive Review of Geographic Routing Protocols in Wireless Sensor Network
To analyses the impact of high mobility, dynamic topologies, scalability and routing due to the more dynamic changes in network. To enhance mobile Ad-hoc network (MANET) self-organization capabilities by geographical rou...
Routing Attack Detection Using Ensemble Deep Learning Model for IIoT
Smart cities, ITS, supply chains, and smart industries may all be developed with minimal human interaction thanks to the increasing prevalence of automation enabled by machine-type communication (MTC). Yet, MTC has subst...