Results 101 to 110 of about 2,740,047 (370)
Supervised Collective Classification for Crowdsourcing
Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainly unsupervised methods that are unaware of the quality of crowdsourced ...
Chen, Pin-Yu +4 more
core +1 more source
Isolation Defines Identity: Functional Consequences of Extracellular Vesicle Purification Strategies
Four extracellular vesicle purification strategies are compared using ovarian‐cancer ascites and ES‐2 cell supernatants. A novel workflow links purification to function by combining particle‐normalized proteomics with matched cell‐free and cell‐based assays.
Christian Preußer +10 more
wiley +1 more source
Sparse Coding on Stereo Video for Object Detection [PDF]
Deep Convolutional Neural Networks (DCNN) require millions of labeled training examples for image classification and object detection tasks, which restrict these models to domains where such datasets are available.
Kenyon, Garrett T. +2 more
core +2 more sources
Customer Churn - Prevention Model – Unsupervised Classification
The strategy of any organization is based on the growth of its customer base, and one of 6 its principles is that selling a product to an existing customer is much more profitable than acquiring 7 a new customer. However, this approach has several opportunities for improvement, since it usu- 8 ally has a totally reactive approach, which does not ...
openaire +2 more sources
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Predicting protein complexes using a supervised learning method combined with local structural information. [PDF]
The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein ...
Yadong Dong, Yongqi Sun, Chao Qin
doaj +1 more source
While many prior works used text mining for automating different tasks related to software bug reports, few works considered the security aspects. This paper is focused on automated classification of software bug reports to security and not-security ...
K. Goseva-Popstojanova, Jacob Tyo
semanticscholar +1 more source
Unsupervised Classification of PolSAR Data Using a Scattering Similarity Measure Derived From a Geodesic Distance [PDF]
In this letter, we propose a novel technique for obtaining scattering components from polarimetric synthetic aperture radar (PolSAR) data using the geodesic distance on the unit sphere.
D. Ratha, A. Bhattacharya, A. Frery
semanticscholar +1 more source
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Inference and Evaluation of the Multinomial Mixture Model for Text Clustering
In this article, we investigate the use of a probabilistic model for unsupervised clustering in text collections. Unsupervised clustering has become a basic module for many intelligent text processing applications, such as information retrieval, text ...
Banerjee +16 more
core +4 more sources

