The Experts below are selected from a list of 459165 Experts worldwide ranked by ideXlab platform
Gurpreet Singh Lehal - One of the best experts on this subject based on the ideXlab platform.
-
named entity recognition system for urdu
International Conference on Computational Linguistics, 2012Co-Authors: Umrinderpal Singh, Vishal Goyal, Gurpreet Singh LehalAbstract:Named Entity Recognition (NER) is a task which helps in finding out Persons name, Location names, Brand names, Abbreviations, Date, Time etc and classifies the m into predefined different categories. NER plays a major role in various Natural Language Processing (NLP) fields like Information Extraction, Machine Translations and Question Answering. This paper describes the problems of NER in the context of Urdu Language and provides relevant solutions. The system is developed to tag thirteen different Named Entities (NE), twelve NE proposed by IJCNLP-08 and Izaafats. We have used the Rule Based approach and developed the various rules to extract the Named Entities in the given Urdu text.
Manish Kumar - One of the best experts on this subject based on the ideXlab platform.
-
recent named entity recognition and classification techniques a systematic review
Computer Science Review, 2018Co-Authors: Archana Goyal, Vishal Gupta, Manish KumarAbstract:Abstract Textual information is becoming available in abundance on the web, arising the requirement of techniques and tools to extract the meaningful information. One of such an important information extraction task is Named Entity Recognition and Classification. It is the problem of finding the members of various predetermined classes, such as person, organization, location, Date/Time, quantities, numbers etc. The concept of named entity extraction was first proposed in Sixth Message Understanding Conference in 1996. Since then, a number of techniques have been developed by many researchers for extracting diversity of entities from different languages and genres of text. Still, there is a growing interest among research community to develop more new approaches to extract diverse named entities which are helpful in various natural language applications. Here we present a survey of developments and progresses made in Named Entity Recognition and Classification research.
N J Cook - One of the best experts on this subject based on the ideXlab platform.
-
the use of digital video recorders dvrs for capturing digital video files for use in both the observer and ethovision
Behavior Research Methods, 2006Co-Authors: J S Church, D G Martz, N J CookAbstract:Before switching a laboratory from analog to digital, for the recording of video files for use in Noldus software such as Ethovision and The Observer, researchers need to proceed with caution. There are obvious advantages in moving to digital recording for behavioral work, including increased storage capacity; no requirement to purchase video tapes; immediate search by Date, Time, or event; digital images are of higher quality; ability to view study sites remotely by Internet connection; and “smart” features, such as motion detection. But before you throw away your Time-lapse video recorders, Time code generators, and video multiplexors, there are some important cautions to take account of. Some research groups have bought digital surveillance systems on the assumption that they work with Ethovision and The Observer, only to be disappointed. The vast majority of systems depend on proprietary compression software that must then be converted to work properly in Ethovision or The Observer.
Wells, R.j. David - One of the best experts on this subject based on the ideXlab platform.
-
Presence/absence and density data for epipelagic tows from 48 stations in the northern Gulf of Mexico from R/V Blazing Seven cruises LF2015A and LF2015B June 2015 and July 2015
NSUWorks, 2017Co-Authors: Rooker, Jay R., Wells, R.j. DavidAbstract:Larval catch data after the oil spill is being used to improve our understanding of the causes of temporal variability as it relates to the Deep Water Horizon oil spill (DWHOS). Bongo and neuston net tows were conducted at 48 stations in both June and July, 2015 in the northern Gulf of Mexico. Cruise data collected at each site included latitude/longitude, Date, Time and environmental data (temperature, salinity, dissolved oxygen). The occurrence and density of selected epipelagic (e.g., billfishes, tunas, dolphinfishes, flyingfishes) and deep pelagic (e.g., lanternfishes, bristlemouths, marine hatchetfishes) fish larvae were quantified and are being used to extend the pre- and post-DWHOS Time series to better understand the drivers of natural variability in abundance for these taxa. Catch data are also being coupled with environmental data to identify high quality (highly suitable) habitat of each species or taxonomic group
-
Cruise data for neuston net and paired bongo net tows from 48 stations in the northern Gulf of Mexico from R/V Blazing Seven cruises LF2015A and LF2015B June 2015 and July 2015
NSUWorks, 2017Co-Authors: Rooker, Jay R., Wells, R.j. DavidAbstract:Shelf and slope waters in the Deep Water Horizon oil spill (DWHOS) area are known to serve as critical spawning, nursery, and foraging habitat of several important oceanic species including billfishes (e.g. blue marlin, white marlin, sailfish), tunas (bluefin tuna, yellowfin tuna), and other pelagic taxa (swordfish, dolphinfishes). The aim of this component was to further investigate potential ecological effects of the DWHOS on pelagic fishes during the early life period. Larval fishes were sampled from 48 stations in the northern Gulf of Mexico and cruise data was collected at each site including latitude/longitude, Date, Time and environmental data (sea surface temperature, salinity, dissolved oxygen, Sargassum biomass) during 2015. Samples were obtained from R/V Blazing Seven cruises LF2015A and LF2015B from June 2015 - July 2015. This dataset report environmental data (temperature, salinity, dissolved oxygen) collected during these cruises
Andreas Savakis - One of the best experts on this subject based on the ideXlab platform.
-
automated event clustering and quality screening of consumer pictures for digital albuming
IEEE Transactions on Multimedia, 2003Co-Authors: Alexander C Loui, Andreas SavakisAbstract:In this paper, algorithms for automatic albuming of consumer photographs are described. Specifically, two core algorithms namely event clustering and screening of low-quality images, are introduced and their performance is evaluated. Event clustering and image quality screening have many applications including albuming services, image management and organization, and digital photofinishing. These are difficult tasks because there is, in general, none (or very limited) contextual information about picture content, and the final interpretation could be subjective. A novel event-clustering algorithm is created to automatically segment pictures into events and subevents for albuming, based on Date/Time metadata information, as well as color content of the pictures. A block-based color histogram correlation technique is developed for image content comparison of general consumer pictures. A new quality-screening algorithm is developed based on object quality measures, to detect problematic images caused by underexposure, low contrast, and camera defocus or movement.
-
automatic image event segmentation and quality screening for albuming applications
The Institute of Electrical and Electronics Engineers, 2000Co-Authors: Alexander C Loui, Andreas SavakisAbstract:In this paper, a system for automatic albuming of consumer photographs is described and its specific core components of event segmentation and screening of low quality images are discussed. A novel event segmentation algorithm was created to automatically cluster pictures into events and sub-events for albuming, based on Date/Time meta data information as well as color content of the pictures. A new quality-screening is developed based on object quality to detect problematic images due to underexposure, low contrast, and camera defocus or movement. Performance testing of these algorithms was conducted using a database of real consumer photos and showed that these functions provide a useful first-cut album layout for typical rolls of consumer pictures. A first version of the automatic albuming application software was rested through a consumer trial in the United States from August to December 1999.
