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Extracting Descriptive Frames from Informational Videos

     Informational videos are becoming increasingly important among all video types. The users spend so much time browsing the informative videos, even if they are not interested in all their topics. Thence, a new method for extracting descriptive frames is presented in this paper that allows users to navigate directly to the topics of their interest in the video. The proposed method consists of three main phases: video preprocessing, video segmentation, and the video separation phase. Firstly, frames are extracted from the videos, resized, and converted to grayscale. Then, the frames are divided into blocks, and the kurtosis moment is calculated for each block. The videos are segmented based on an examination of the differences between the features of the kurtosis moment. Lastly, the informative frames are grouped into a separate video after they are distinguished from the uninformative ones using the clustering technique. The results demonstrated the functional effectiveness of the proposed method. According to the accuracy and F1-Score measures, it has a performance of up to 100%. Moreover, the video is significantly summarized by reducing the duration to less than 1% of its original time.

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Sat Apr 01 2023
Journal Name
The Ocular Surface
Detecting dry eye from ocular surface videos based on deep learning

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Publication Date
Fri Mar 20 2009
Journal Name
Ijcsns International Journal Of Computer Science And Network Security
Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images

Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Induction informational, informational use, the behavior of the product and user information.

Abstract:

This study seeks to shed light on the important processes are linked to the impact of accounting information on the behavior of producer and user of information and are urging informational and informational use. That accounting as a system of accounting information and functions of the delivery of information to decision makers Under behavioral entrance to the formulation of accounting theory should be taken into account Othertlk accounting information in the behavior of the decision maker which requires an explanation of human behavior and predictable.

On the other hand that the accounting information that should be delivered to the decision maker will affect your beha

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Publication Date
Sun Mar 04 2018
Journal Name
Iraqi Journal Of Science
Heartbeat Amplification and ECG Drawing from Video (Black and White or Colored Videos)

Electrocardiography (ECG or EKG) is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. The main idea is how to detect activity of the heart from skin that appears in video without using electrodes. This paper, proposes an algorithm that works on analyzing video frames to detect heartbeats from tiny changes that happen in a skin color luminance (brightness) and then using them to amplifying heartbeat and drawing ECG. The results show that the heartbeat was detected and amplified and ECG was drawing from any part of the human body in different situations and from different video.

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
The Role of Informational Environment in Building Smart City

The research addresses smart city concept as it is the latest urban design trends, by the investment of the capabilities of human, and artificial intelligence for the sake of the advancement of the city. The concept of a smart city is described as one of the most important manifestations of the information revolution, with the end of the twentieth, and the beginning of twenty – first century, The research attributes the emergence of the concept to: deficiencies of means, and traditional methods in building and development of cities, as well as The significant increase in the number of city and global metropolises dwellers. So, smart city approach has been adopted, along with innovative principles and methods which cons

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Publication Date
Sat Nov 01 2014
Journal Name
I-manager's Journal On Information Technology
AN ENHANCED METHOD FOR SPRITE EXTRACTING

The extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.

Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Reflections informational monitoring in Creative marketing systems

Abstract:                                                                                                      

         The research aims to measure the impact of infor

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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
EXTRACTING PECTIN FROM TOMATOES AND BEET PEELS AND USING IT IN THE MANUFACTURE OF YOGURT AND COMPARING THEM

Pectin is available in many plants and in this study, the peels of tomatoes and beet were used to be an economical source of pectin production instead of dumping it with waste or using it as animal feed. The pectin extracted from the peels using different solutions, namely citric acid (2 M), oxalic acid (2%) and hydrochloric acid (0.5 M) the outcome of the extraction methods, 7. 1%, 6% and 11% respectively for tomatoes peels, while the pectin of beet peels were 8%, 6.5%, and 8.3%, and the highest percentage obtained in the manner of hydrochloric acid adopted in the manufacture of yogurt.Yogurt was manufactured with four treatments, in the first treatment standard pectin was added and the second treatment in addition to the pectin extracted

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Data Mining Methods for Extracting Rumors Using Social Analysis Tools

       Rumors are typically described as remarks whose true value is unknown. A rumor on social media has the potential to spread erroneous information to a large group of individuals. Those false facts will influence decision-making in a variety of societies. In online social media, where enormous amounts of information are simply distributed over a large network of sources with unverified authority, detecting rumors is critical. This research proposes that rumor detection be done using Natural Language Processing (NLP) tools as well as six distinct Machine Learning (ML) methods (Nave Bayes (NB), random forest (RF), K-nearest neighbor (KNN), Logistic Regression (LR), Stochastic Gradient Descent (SGD) and Decision Tree (

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