Character-level linguistic biomarkers for precision assessment of cognitive decline: a symbolic recurrence approach. [PDF]
Mekulu K, Aqlan F, Yang H.
europepmc +1 more source
Delineating SARS-CoV-2 spike protein and antibodies interaction interfaces via siamese neural networks: A geometric and image-based analysis. [PDF]
Loreti G +6 more
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Efficient multi-finger vein recognition using layer-wise progressive MobileNet fine-tuning and a Dense-Head Probabilistic Siamese Network. [PDF]
Alaerjan AS +3 more
europepmc +1 more source
Unsupervised seamless UAV image stitching via dense prediction. [PDF]
Chen J +5 more
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A quartet-based approach for inferring phylogenetically informative features from genomic and phenomic data. [PDF]
Brandenburg VB, Hack BL, Mosig A.
europepmc +1 more source
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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.
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Siamese Ballistics Neural Network
2019 IEEE International Conference on Image Processing (ICIP), 2019Firearm identification is crucial in many investigative scenario. The crime scene often contains traces left by firearms in terms of bullets and cartridges. Traces analysis is a fundamental step in the Forensics Ballistics Analysis Process to identify which firearm fired a specific cartridge.
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Siamese Network for Salivary Glands Segmentation
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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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Siamese Network for Classification with Optimization of AUC
2019It is known that RankSVM can optimize area under the ROC curve (AUC) for binary classification by maximizing the margin between the positive class and the negative class. Since the objective function of Siamese Network for rank learning is the same as RankSVM, Siamese Network can also optimize AUC for binary classification. This paper proposes a method
Hideki Oki, Jun'ichi Miyao, Takio Kurita
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