Results 41 to 50 of about 9,360,077 (298)
Neural-Network and k-Nearest-neighbor Classifiers
, 1991 The performance of a state-of-the-art neural network classifier for hand-written digits is compared to that of a k-nearest-neighbor classifier and to human performance.
Sackinger, E., Bromley, J.
core +5 more sources
FEBS Letters, EarlyView.Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
On the Robustness of Deep K-Nearest Neighbors [PDF]
2019 IEEE Security and Privacy Workshops (SPW), 2019 Published at Deep Learning and Security Workshop 2019 (IEEE S&P)
Chawin Sitawarin, David A. Wagner 0001
openaire +3 more sources
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Nearest-Neighbor-Based Active Learning for Rare Category Detection
, 2018 Rare category detection is an open challenge for active learning, especially in the de-novo case (no labeled examples), but of significant practical importance for data mining - e.g.
Jaime G. Carbonell (5361842) +1 more
core +2 more sources
A Continuous k-Nearest Neighbor Query Method for Moving Data in Obstructed Spaces
Journal of Harbin University of Science and Technology, 2018 For the nearest neighbor query problem of continuous moving objects in spatio-temporal databases, the COpKNN (continuous obstructed possible k-nearest neighbor) query is proposed: in a two-dimensional space, given a moving query point q, a set of moving ...
WAN Jing +3 more
doaj +1 more source
Structure‐forward targeting of claudins with synthetic binders
FEBS Letters, EarlyView.Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley +1 more source
Fast Approximate Complete-data k-nearest-neighbor Estimation
Austrian Journal of Statistics, 2020 We introduce a fast method to estimate the complete-data set of k-nearest-neighbors.This is equivalent to finding an estimate of the k-nearest-neighbor graph of the data. The method relies on random normal projections.
Alejandro Murua, Nicolas Wicker
doaj +1 more source
Pilar Nusa Mandiri, 2022 Classification of blood donor data at UTD PMI Bali Province by applying the C4.5 and K-Nearest Neighbor algorithms. The number of blood donor data donors is 34,948, of which 90% of the data, namely 31,454 is used as training data.
Ni Ketut Melly Astuti +2 more
doaj +1 more source
Liver organoids: modelling complexity in homeostasis and disease
FEBS Letters, EarlyView.Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
wiley +1 more source