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Instance segmentation
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Lecture Artificial intelligence: k-means clustering. This lecture provides students with content including: group together similar instances high intra-cluster similarity and low inter-cluster similarity; document clustering; customer segmentation; recommendation engines; image compression;... Please refer to the detailed content of the lecture!
20p
codabach1016
03-05-2024
3
0
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In this paper, we introduce a novel method that combines the original Mask R-CNN pipeline and 3D algorithms branch to preserve and classify the edge region. This results from the improvement of the performance of Mask R-CNN in detailed segmentation.
8p
viporsche
25-10-2022
4
2
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In this paper, we introduce a segmentation system that can automatically measure the fetal head circumference (HC) with a minimum error rate by using ultrasound images. With the optimized results, the HC can be applied to estimate the gestational age and keep track of the health of the infants.
8p
visherylsandberg
18-05-2022
9
2
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Several spectrally based pattern recognition problems appear in many areas e.g., image segmentation in computer vision, alignment of protein-protein interaction networks in bio-informatics, recognizing hard instances for combinatorial optimization problems such as the travelling salesman problem.
17p
vinguyentuongdanh
19-12-2018
33
5
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SQL Server was originally the Microsoft rebadged version of the Sybase relational database. It is only available on Windows platforms. Current version (July 2010) is SQL Server 2008 R2. The two principal differences between SQL Server/Sybase and Oracle are: 1. SQL Server has no undo or rollback segments and therefore no rollback/commit functionality, or read consistent data views; other than what little can be accommodated from the on line redo logs. 2. SQL Server architecture is: 1 host machine to 1 or more Instances to many Databases.
48p
thetam263
05-06-2013
109
4
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This paper presents a Bayesian decision framework that performs automatic story segmentation based on statistical modeling of one or more lexical chain features. Automatic story segmentation aims to locate the instances in time where a story ends and another begins. A lexical chain is formed by linking coherent lexical items chronologically. A story boundary is often associated with a significant number of lexical chains ending before it, starting after it, as well as a low count of chains continuing through it.
4p
hongphan_1
15-04-2013
38
1
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Using Online Redo Log Files Online redo log files provide the means to redo transactions in the event of a database failure. Every transaction is written synchronously to the Redo Log Buffer, then gets flushed to the online redo log files in order to provide a recovery mechanism in case of media failure. (With exceptions such as direct load inserts in objects with the NOLOGGING clause enabled.) This includes transactions that have not yet been committed, undo segment information, and schema and object management statements.
30p
trinh02
28-01-2013
58
4
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On the one hand, some have interpreted this approach as a relaxation of governance standards on lower tiers or on the market more generally. 21 For instance, Alternext-listed companies are not subject to any of the corporate governance codes applicable in the four jurisdictions covered by the Euronext main market. On the other hand, insofar as these new segments mostly do not compete head-to-head with old exchanges for the same listings the approach can equally be seen as an adaptation of governance requirements to suit the size and type of prospective issuers.
0p
bocapchetnguoi
05-12-2012
57
1
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Navigation Bar Revisited 5 6 7 8 9 10 11 12 public class NavigationBar extends MovieClip { private var _navData:Array; public function NavigationBar(navData:Array) { _navData = navData; build(); } In the next code segment, the build() method uses a for loop to add each button to the navigation bar. The loop first creates an instance of the MenuButtonMain class, passing the name of the button as a string for the button’s label.
0p
yukogaru13
30-11-2010
75
14
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