THE DISTRIBUTION OF THE FLORA IN THE ALPINE ZONE.1

By P. Jaccard. 1912

Subfields: Computer Vision and Pattern Recognition

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Citations in the corpus

Deduplicating Training Data Makes Language Models Better (2021, methodology): “We can then use hash functions to approximate the Jaccard Index (Jaccard, 1912): If the Jaccard Index between d i and d j is sufﬁ-ciently high, it is likely that documents are approximate matches of each other.”
The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only (2023, background): “The ratio of matching hashes between two documents approximates the Jaccard Similarity (Jaccard, 1912) of the sets of their unique n-grams (the sets being di and dj):”
Weakly Supervised Action Labeling in Videos under Ordering Constraints (2014, methodology): “This measure is similar to the standard Jaccard measure used for comparing ensembles [16].”
Generative Kernels for Tree-Structured Data (2018, unknown): “We propose the Jaccard similarity [42], that is a well known metric for comparing multisets and that, in its most general form, writes as where f is a suitable function (e.g. cardinality).”
RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation (2023, methodology): “This model transforms the query and candidate code snippets into sets of tokens and calculates their similarity using the Jaccard index (Jaccard, 1912), computed as Jaccard ( S q , S c ) = | S q ∩ S c | | S q ∪ S c | , where S q and S c represent the tokens of the query and candidate code snippets,…”
Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation (2004, methodology): “Other measures used in practice include measures of spatial overlap, such as the Dice and Jaccard Similarity Coefficients [11], [ 12 ].”
Tree diversity and population structure in undisturbed and human-impacted stands of tropical wet evergreen forest in Arunachal Pradesh, Eastern Himalayas, India (2003, methodology): “The similarity index (community coefficient) among different stands was calculated according to Jaccard (1912): C 5j / a1b2js dj where j is the number of species common to both stands, a the number of species in stand A and b the number of species in stand B.”
Modified TWINSPAN classification in which the hierarchy respects cluster heterogeneity (2009, unknown): “dissimilarity of all pairs of sites (Jaccard 1912; S rensen 1948; Koleff et al. 2003); and total inertia,”
The relationship between species replacement, dissimilarity derived from nestedness, and nestedness (2012, background): “However, the use of similarity or dissimilarity measures to analyse patterns of variation in species composition is in fact much older (e.g. Jaccard, 1912; Simpson, 1943).”
U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications (2020, background): “Intersection over union (IoU) loss, derived from the Jaccard index, measures the ratio of the intersection of the samples to their union [363].”
Non-indigenous ungulates as a threat to biodiversity (2009, methodology): “To investigate the similarity of ungulate assemblages introduced to different countries, a cluster analysis of percentage Jaccard similarity (Jaccard, 1912) between the introduced ungulate assemblages of country pairs, was performed in Primer v 5.”
FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic (2020, methodology): “To account for this fact, we do not compare fingerprints as an exact match, but instead base their comparison on the Jaccard similarity [35].”
Automated distance estimation for wildlife camera trapping (2022, background): “SORT connects these animal detections over all frames to cohesive tracks based on a Kalman-Filter framework (Chen, 2012) and the association metric of two visual detections by Intersection over Union (IoU) (Jaccard, 1912).”
A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI (2016, background): “• The Jaccard index (Jaccard, 1912) is a measure of overlap or similarity between two contour areas, and is defined as: Similar to the Dice index, the Jaccard index varies from zero to unity, with unity representing perfect correspondence with the ground truth.”
Competition between photochemical and biological degradation of dissolved organic matter from the cyanobacteria Microcystis aeruginosa (2015, methodology): “The Jaccard similarity index (JSI) was used to assess similarity between E-DOM and IDOM regarding molecular composition and was calculated as JSI 5 # of formulae common to both samples 3 (# formulae unique to E-DOM 1 # formulae unique to I-DOM 1 # formulae common to both samples)21 (Jaccard 1912).”