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Local Semantic Siamese Networks for Fast Tracking
IEEE Transactions on Image Processing, 2020Learning a powerful feature representation is critical for constructing a robust Siamese tracker. However, most existing Siamese trackers learn the global appearance features of the entire object, which usually suffers from drift problems caused by partial occlusion or non-rigid appearance deformation.
Zhiyuan Liang, Jianbing Shen
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Siamese Networks for Chromosome Classification
2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017Karyotying is the process of pairing and ordering 23 pairs of human chromosomes from cell images on the basis of size, centromere position, and banding pattern. Karyotyping during metaphase is often used by clinical cytogeneticists to analyze human chromosomes for diagnostic purposes.
null Swati +4 more
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Siamese-ResNet: Implementing Loop Closure Detection based on Siamese Network
2018 IEEE Intelligent Vehicles Symposium (IV), 2018Deep learning has made significant breakthroughs in the tasks of image classification, detection, segmentation, etc. However, the application of deep learning in robotics is still scarce. SLAM is a fundamental problem in robotics and loop closure detection is an important part of SLAM. This paper attempts to use supervised learning methods to solve the
Kai Qiu +4 more
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Siamese Neural Networks: An Overview
2020Similarity has always been a key aspect in computer science and statistics. Any time two element vectors are compared, many different similarity approaches can be used, depending on the final goal of the comparison (Euclidean distance, Pearson correlation coefficient, Spearman's rank correlation coefficient, and others). But if the comparison has to be
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Face Recognition Using Siamese Network
2020Face recognition has become very popular in biometrics in recent time, especially after the availability of GPU-based processing technology and ease of implementing deep learning methodologies. Still, it is treated as computationally expensive when the training database is large and efficiency is in stake when little data is available for training. One
Srinibas Rana, Dakshina Ranjan Kisku
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Palmprint Recognition Using Siamese Network
2018Recently, palmprint representation using different descriptors under the incorporation of deep neural networks, always achieves significant recognition performance. In this paper, we proposed a novel method to achieve end-to-end palmprint recognition by using Siamese network.
Dexing Zhong, Yuan Yang, Xuefeng Du
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Attributed Network Embedding via a Siamese Neural Network
2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2019Recently, network embedding has attracted a surge of attention due to its ability to automatically extract features from graph-structured data. Though network embedding method has been intensively studied, most of the existing approaches pay attention to either structures or attributes.
Jiong Wang +3 more
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Predicting Cherry Quality Using Siamese Networks
2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), 2020The cherry industry is a rapidly growing sector of New Zealand’s export merchandise and, as such, the accuracy with which pack-houses can grade cherries during processing is becoming increasingly critical. Conventional computer vision systems are usually employed in this process, yet they fall short in many respects, still requiring humans to manually ...
Yerren van Sint Annaland +2 more
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Word Spotting Using Convolutional Siamese Network
2018 13th IAPR International Workshop on Document Analysis Systems (DAS), 2018We present a method for word spotting using convolutional siamese network. A convolutional siamese network employs two identical convolutional network to rank similarity between two input word images. Once the network is trained, it can then be used to spot not just words with varying writing styles and backgrounds but also to spot out of vocabulary ...
Berat Kurar Barakat +2 more
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Snake Image Classification using Siamese Networks
Proceedings of the 2019 3rd International Conference on Graphics and Signal Processing, 2019Research into deep learning models suitable for small data sets is still in an immature state since it has received less attention from the machine learning community. Identifying a snake species using images, is a classification problem which has a number of medical, educational and safety-related importance but no large data set.
Chamath Abeysinghe +2 more
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