Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Haozhen Zhao"'
Publikováno v:
Computational and Mathematical Methods in Medicine.
In order to improve the prediction effect of sports training performance and improve the effect of sports training, this paper classifies the sports training image area, refines the image into different areas, finds suspicious areas, and completes th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a73c77cc49a30eb5e83fb49d32626531
Protecting privileged communications and data from inadvertent disclosure is a paramount task in the US legal practice. Traditionally counsels rely on keyword searching and manual review to identify privileged documents in cases. As data volumes incr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d370ca38b7fb9376b1905623035e636
http://arxiv.org/abs/2112.08606
http://arxiv.org/abs/2112.08606
During the past decade breakthroughs in GPU hardware and deep neural networks technologies have revolutionized the field of computer vision, making image analytical potentials accessible to a range of real-world applications. Technology Assisted Revi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d3c94699184fa1dd9af36ce5c7fff76
http://arxiv.org/abs/2112.08604
http://arxiv.org/abs/2112.08604
Autor:
Rishi Chhatwal, Haozhen Zhao, Robert Keeling, Jianping Zhang, Peter Gronvall, Nathaniel Huber-Fliflet
Publikováno v:
IEEE BigData
Protecting privileged communications and data from disclosure is paramount for legal teams. Legal advice, such as attorney-client communications or litigation strategy are typically exempt from disclosure in litigations or regulatory events and are v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f810956e4860f242ea1dd24222f7ac3
Publikováno v:
IEEE BigData
In eDiscovery, it is critical to ensure that each page produced in legal proceedings conforms with the requirements of court or government agency production requests. Errors in productions could have severe consequences in a case, putting a party in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c41102ffa4dbd75ed1da2cf01b71aba
https://doi.org/10.1109/bigdata50022.2020.9378313
https://doi.org/10.1109/bigdata50022.2020.9378313
Publikováno v:
IEEE BigData
Companies regularly spend millions of dollars producing electronically-stored documents in legal matters. Recently, parties on both sides of the 'legal aisle' are accepting the use of machine learning techniques like text classification to cull massi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c77230db6c17dd4d6d877f841b60a5d
http://arxiv.org/abs/1912.09501
http://arxiv.org/abs/1912.09501
Publikováno v:
IEEE BigData
Though technology assisted review in electronic discovery has been focusing on text data, the need of advanced analytics to facilitate reviewing multimedia content is on the rise. In this paper, we present several applications of deep learning in com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d0431f22cc539e73c90867bd8e11d30
https://doi.org/10.1109/bigdata47090.2019.9006551
https://doi.org/10.1109/bigdata47090.2019.9006551
Publikováno v:
IEEE BigData
Predictive coding, once used in only a small fraction of legal and business matters, is now widely deployed to quickly cull through increasingly vast amounts of data and reduce the need for costly and inefficient human document review. Previously, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de0e2fd2d2904baaab940e7403f1eb66
http://arxiv.org/abs/1904.01718
http://arxiv.org/abs/1904.01718
Autor:
Rishi Chhatwal, Haozhen Zhao, Peter Gronvall, Nathaniel Huber-Fliflet, Robert Keeling, Jianping Zhang
Publikováno v:
IEEE BigData
In today's legal environment, lawsuits and regulatory investigations require companies to embark upon increasingly intensive data-focused engagements to identify, collect and analyze large quantities of data. When documents are staged for review the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a463c5781f7af9e1ed4b4e6050567cfa
http://arxiv.org/abs/1904.01721
http://arxiv.org/abs/1904.01721
Publikováno v:
IEEE BigData
One type of machine learning, text classification, is now regularly applied in the legal matters involving voluminous document populations because it can reduce the time and expense associated with the review of those documents. One form of machine l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb37923d49341f456c4b8102777c5957
http://arxiv.org/abs/1904.01719
http://arxiv.org/abs/1904.01719