Audiovisual Information-Based Highlight Extraction

2015 ◽  
pp. 135-144
Keyword(s):  
Highlight Extraction

Transition logo detection for sports videos highlight extraction

2006 ◽  
Author(s):  
Po-Chyi Su ◽  
Yu-Wei Wang ◽  
Chien-Chang Chen
Keyword(s):  
Sports Videos ◽  
Highlight Extraction

Highlight extraction in soccer videos

2004 ◽  
Author(s):  
J. Assfalg ◽  
M. Bertini ◽  
C. Colombo ◽  
A. Del Bimbo ◽  
W. Nunziati
Keyword(s):  
Highlight Extraction

scholarly journals Brain Tumor Discovery Using Image Preprocessing

2020 ◽  
Vol 11 (4) ◽  
pp. 6870-6875
Author(s):  
Prem Jacob T ◽  
Polakam Sukanya ◽  
Thatiparthi Madhavi
Keyword(s):  
Big Data Analytics ◽  
Malignant Growth ◽  
Data Types ◽  
Mri Scan ◽  
Tree Disease ◽  
Cancer Prediction ◽  
Wired Communication ◽  
The Brain ◽  
Highlight Extraction ◽  
Insight Into

The segmentation of attractive reverberation images assumes a critical job in therapeutic fields since it removes the required territory from the picture. Generally, there is no unique methodology for the segmentation of the picture. Tumour division from MRI information is a critical tedious manual undertaking performed by therapeutic specialists. In this paper, the Brain Cancer prediction System has been detailed. The framework utilizes PC based methods to recognize tumor squares and classify the tumour utilizing Artificial Neural Network. The picture preparing strategies, for example, histogram evening out, picture division, picture improvement, and highlight extraction, have been produced for the location of the cerebrum tumor in the MRI pictures of the malignant growth Detected patients. This paper focuses around another and exceptionally acclaimed algorithm for mind tumor division of MRI scan image by ANN and SVM algorithms to analyze precisely the locale of malignant growth as a result of its straightforwardness and computational proficiency. The MATLAB output will be shown in pc and furthermore observe the yield to insert framework utilizing wired communication. To the best of our insight into the zone of therapeutic big data analytics, none of the current work concentrated on the two data types. Contrasted with a few runs of the typical algorithms, the computation precision of our proposed algorithm achieves 94.8% with an assembly speed, which is quicker than that of the Decision tree disease hazard prediction.

Extract Soccer Video Highlights with Modified CRF

2014 ◽  
Vol 926-930 ◽  
pp. 3426-3429
Author(s):  
Nai Gu Huang ◽  
Yang Yi ◽  
Yu Lin Wang ◽  
Peng Fei Zhu
Keyword(s):  
Boolean Function ◽  
Bayesian Network ◽  
Video Analysis ◽  
Posterior Probability ◽  
Conditional Random Field ◽  
Actual Situation ◽  
Soccer Video ◽  
Soccer Video Analysis ◽  
Highlight Extraction ◽  
Original Feature

Soccer video analysis is attracting much attention. In this paper, we propose a modified conditional random field (CRF) model to extract the highlights of an entire soccer video. Highlight extraction in soccer video is essentially a kind of timing annotation problems, so the commonly used CRF model is adopted to solve this problem in this paper. Meanwhile, Boolean function is normally used as feature function in the CRF model, which will result in a hard association between observed variables and highlight variables. By introducing Bayesian network to model the observed variables and replacing the original feature function with posterior probability calculated with Bayesian network, hard association is transformed into soft association, which makes the model more close to the actual situation. Experimental results show that the proposed algorithm has achieved good results.

scholarly journals Hook Worm Detection and its Classification Techniques

2020 ◽  
Vol 8 (6) ◽  
pp. 1795-1798
Keyword(s):  
Capsule Endoscopy ◽  
Complex Structure ◽  
Wireless Capsule Endoscopy ◽  
Neural Systems ◽  
Worm Detection ◽  
Classification Techniques ◽  
The One ◽  
Hook Worm ◽  
Wireless Capsule ◽  
Highlight Extraction

Wireless Capsule endoscopy (WCE) has transformed into a by and large used demonstrative strategy to look at some fiery infections and disarranges. Customized and completely robotized hookworm recognition and characterization models are testing task because of low nature of pictures, nearness of incidental issues, complex structure of gastrointestinal and various appearances to the extent shading and surface. There are a few endeavours were made to thoroughly research the robotized hookworm discovery from WCE pictures. A definite review is taken for identifying Hookworm in Endoscopy picture and its partner pre and post preparing specialized application. A profound report on AI system and highlight extraction approaches were examined. The different advances engaged with Hookworm location utilizing neural systems alongside their sorts were additionally talked about. The significant highlights which can be utilized for extricating the one of a kind highlights were considered.

scholarly journals Application of Artificial Neural Network in Electrical Power System

2018 ◽  
Vol 9 (1) ◽  
pp. 77
Author(s):  
P. Palanichamy
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
System Performance ◽  
Electrical Power ◽  
Electrical Machines ◽  
Electrical Power System ◽  
Artificial Neural ◽  
Information Components ◽  
Highlight Extraction

The artificial neural network used to detect the fault in electrical machines and can increase the function of new entry detection when compared to the conventional method. In proposed artificial neural network has increased the precision and stability of system performance.<strong> </strong>The time-area vibration signs of a pivoting machine with ordinary and flawed apparatuses are handled for highlight extraction. The separated elements from unique and preprocessed signs are utilized as contributions to both classifiers in view of ANNs and SVMs for two-class (typical or blame) acknowledgment. The quantity of hubs in the concealed layer, if there should be an occurrence of ANNs, and the extend basis work section parameter, in the event of SVMs, alongside the choice of information components are enhanced utilizing genetic algorithm (GAs).

scholarly journals Robotic Handwritten Kannada Character Recognition using Neural Network

2019 ◽  
Vol 8 (10) ◽  
pp. 2498-2502 ◽  
Keyword(s):  
Neural Network ◽  
Character Recognition ◽  
Component Analysis ◽  
Neural System ◽  
Feed Forward ◽  
Essential Component ◽  
Kannada Language ◽  
Number Of Classes ◽  
Highlight Extraction

Data preparing and the board is basic now a days. In this paper, programmed preparing of structures written in Kannada language is considered. A reasonable pre-preparing procedure is introduced for separating written by hand characters. Essential Component Analysis (PCA) and Histogram of arranged Gradients (HoG) are utilized for highlight extraction. These highlights are sustained to multilayer feed forward back spread neural system for arrangement. Just 57 characters are utilized for acknowledgment. Exhibitions of two highlights are looked at for changed number of classes. Hoard is found to have preferred acknowledgment exactness over PCA as number of classes expanded. This is actualized in Visual Studio 2010 utilizing Open CV library

scholarly journals Segmentation Images Using Improved Genetic Algorithm

2019 ◽  
Vol 8 (S3) ◽  
pp. 81-84
Author(s):  
Kailasam Leelavathi ◽  
T. Sudha
Keyword(s):  
Genetic Algorithm ◽  
Improved Genetic Algorithm ◽  
Dynamic Learning ◽  
New Methodologies ◽  
Highlight Extraction

With the expanding openness to new advancements, the principle issues in locale acknowledgment of remote detecting pictures are: (1) arrangement techniques are reliant on the division quality; and (2) the choice of delegate tests for preparing. The significant test is that the examples shown by the client are not in every case enough to characterize the best division scale. Besides, the sign of tests can be expensive, since it regularly requires visiting considered places in loco. The choice of delegate tests, then again, was bolstered in this work by the improvement of another intelligent characterization approach based on dynamic learning. Critical commitments were likewise acquired concerning the depiction of areas in remote detecting pictures by methods for: an assessment investigation of 19 descriptors; and two new methodologies for accelerating highlight extraction from a progressive system of sectioned districts.

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