Neural Networks for Fingerprint Recognition

By Pierre Baldi, Yves Chauvin. 1993

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Citations in the corpus

Deep learning in neural networks: An overview (2014, methodology): “, 1990a) (CAP depth 5) and on fingerprint recognition (Baldi and Chauvin, 1993); similar CNNs were used commercially in the 1990s.”
Deep Metric Learning for Person Re-identification (2014, background): “Although good experimental results have been obtained in [3], [14] and [15], their disadvantages are lacking implementation details and lacking comparison with other methods.”
Graph Matching Networks for Learning the Similarity of Graph Structured Objects (2019, background): “Siamese networks have achieved great success in many visual recognition and verification tasks (Bromley et al., 1994; Baldi & Chauvin, 1993; Koch et al., 2015; Bertinetto et al., 2016; Zagoruyko & Komodakis, 2015).”
Deep Metric Learning for Practical Person Re-Identification (2014, background): “In the same year, a neural network [19] with similar structure was proposed for fingerprint verification.”
An Introduction to Neural Information Retrieval (2018, unknown): “Siamese networks Siamese networks were originally proposed for comparing fingerprints [Baldi and Chauvin, 1993] and signatures [Bromley et al.”
A Neural Support Vector Network architecture with adaptive kernels (2000, methodology): “Trainable parametric similarity measures can now be used, that were designed to incorporate prior knowledge specific to the task at hand (such as those proposed in [4, 2]).”
Deep Learning Localizes and Identifies Polyps in Real Time with 96% Accuracy in Screening Colonoscopy (2018, methodology): “Deep learning has been successfully applied to many areas of science and technology 16 , such as computer vision 17,18,19,20,21 , speech recognition 22 , natural language processing 23 , games 24,25 , particle physics 26,27 , organic chemistry 28 , and biology 29,30,31,32,33,34 , to name just a few…”
Optimization Beyond the Convolution: Generalizing Spatial Relations with End-to-End Metric Learning (2017, methodology): “[1], we use a variation of the siamese architecture [2], [3] to train a convolutional neural network as a function that maps an input point cloud of a scene consisting of two objects to the metric space such that the Euclidean distance between points”
Signature Verification Using A "Siamese" Time Delay Neural Network (1993, methodology): “A similar Siamese architecture was independently proposed for fingerprint identification by Baldi and Chauvin (1992).”
Detecting Cardiovascular Disease from Mammograms with Deep Learning (2017, unknown): “volutional neural network (CNN) architectures [37], [38] in particular have led to several successful pattern classifica-”