Image Classification Using Bag of Visual Words (BoVW)

Rafal Sameer

doi:10.22401/ANJS.21.4.11

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Publication Date

Sat Dec 01 2018

Journal Name

Al-nahrain Journal Of Science

Volume

21

DOI

10.22401/ANJS.21.4.11

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Image Classification Using Bag of Visual Words (BoVW)

SIFT

Euclidean distance

classification

k-nearest neighbor

Bag of Visual Words.

Rafal Sameer

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In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

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Publication Date

Thu Feb 07 2019

Journal Name

Journal Of The College Of Education For Women

SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS

Dr. Sadiq jassim

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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

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Publication Date

Sat Mar 29 2025

Journal Name

Journal Of Studies And Researches Of Sport Education

The effect of using the educational bag on the level of learning some offensive skills with the epee weapon

The effect of using the educational bag on the level of learning some offensive skills with the epee weaponDr. Lamia Hassan Al-Diwan

D. Fatima Abdel-Maliki

Dr. Kholoud Laith Abdel Karim2005 Technical and technological development has been increasing day after day and has included all areas of life

including the educational process

which has benefited from technologies such as (computer

video

and pictorial models) in introducing them as tools to aid the learning process. Educational packages have proven their effectiveness in education as they prepare learners with different areas of experience. Sensory audio-visual

through which the learner acquires different educational experiences through interaction

practice

participation

and communication with the data of the surrounding environment through the diversity of knowledge sources that suit his inclinations and needs. The research aimed to prepare an educational bag to teach some offensive skills in the epee weapon. And to find out the effect of using the proposed educational bag on the level of learning some offensive skills in the epee weapon. We hypothesized that the proposed educational package has a positive impact on the level of learning some offensive skills with the epee weapon. There were statistically significant differences in testing the level of learning some offensive skills with the epee weapon between the post-tests of the experimental and control groups

and in favor of the experimental group. The researchers used the experimental method to suit the nature of solving the research problem

and the research sample was chosen intentionally from the girls’ fencing club players (beginners) in the governorate. Basra for the year 2005. The number of players was (16)

which represented the entire study population. The experiment was conducted in the sports hall of the South Oil Sports Club in Basra. We concluded that the educational package has a positive impact on the level of learning some offensive skills in the epee weapon. There were statistically significant differences in the learning level test for some offensive skills in the epee weapon between the experimental group and the control group in the post-tests and in favor of the experimental group. We recommended the necessity of using the proposed educational curriculum to learn some offensive skills in the epee weapon in fencing lessons or in sports clubs. Adopting modern techniques in training

teaching or teaching fencing skills and searching for new methods. Conducting similar studies on other skills or different samples.Keywords: educational bag

offensive skills with an epee weapon

fencing game. Teaching methods. Basra Girl Sports ClubLamya Hassan Aldewan [email protected] of Basra - College of Education and Sports Scienceshttps://orcid.org/0000-0003-0377-6915 Keywords educational bag

offensive skills with an epee weapon

fencing game. Teaching methods. Basra Girl Sports Club

‏Lamyaa

Fatima

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Publication Date

Sat Apr 15 2023

Journal Name

Journal Of Robotics

A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification

support vector machine (SVM)

image classification

hybrid learning

VGG-16 deep learning model

Mohanad

Muna

Dheyaa

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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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(4)

(2)

Publication Date

Thu Apr 27 2017

Journal Name

Ibn Al-haitham Journal For Pure And Applied Sciences

New Adaptive Satellite Image Classification Technique for Al habbinya Region West of Iraq

:Image Processing and Analysis

Supervised Classification

Empirical Conditions

ArcGIS

Remote Sensing

Thematic Mapper (TM).

Taghreed A.

Amaal J.

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Developing a new adaptive satellite images classification technique, based on a new way of merging between regression line of best fit and new empirical conditions methods. They are supervised methods to recognize different land cover types on Al habbinya region. These methods should be stand on physical ground that represents the reflection of land surface features. The first method has separated the arid lands and plants. Empirical thresholds of different TM combination bands; TM3, TM4, and TM5 were studied in the second method, to detect and separate water regions (shallow, bottomless, and very bottomless). The Optimum Index Factor (OIF) is computed for these combination bands, which realized

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Publication Date

Sat Oct 03 2009

Journal Name

Proceeding Of 3rd Scientific Conference Of The College Of Science

Research Address: New Multispectral Image Classification Methods Based on Scatterplot Technique

Taghreed

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Publication Date

Tue Mar 15 2022

Journal Name

Al-academy

The semiotics of the visual image of women in the discourse of empowerment, Saudi Arabia Kingdom as a model

Semiotics

Visual Image

Discourse of empowerment

Nawal

Ebtsam

Sourour

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We studied, in this paper, the semiotics of the visual image of women in the discourse of empowerment, through three models of advertising images expressing the particularities of the Saudi Arabian environment.

We aim to know how the mark operates and how it is interpreted, as a semantic process in which the meaning ranges from description to interpretation, and we studied two hypotheses:

-The advertising image is a structure in which the mark corresponds to the reality and the discourse to the context.

-The significance is not found in the visual sign or in the textual sign of the advertising image, but in the creative event that opens up to the social, cultural, and psychological context, and creates a field of dia

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Publication Date

Sat Jan 01 2022

Journal Name

Turkish Journal Of Physiotherapy And Rehabilitation

classification coco dataset using machine learning algorithms

learning Machine

classification

MCOCO dataset

K Nearest Neighbor's

Stochastic Gradient Descent learning (SGD)

Logistic Regression Algorithm(LR)

and Multi-Layer Perceptron (MLP).

Rasool

Bushra

Raaid

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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

Publication Date

Sat Feb 02 2019

Journal Name

Journal Of The College Of Education For Women

Poetical Words

أ.د .داود

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Poetical Words

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Publication Date

Tue Dec 03 2013

Journal Name

Ibn Al-haitham Journal For Pure And Applied Science

New adaptive satellite image classification technique for al Habbinya region west of Iraq

Taghreed

...Show More Authors

Publication Date

Sat Apr 15 2023

Journal Name

Journal Of Robotics

A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification

Mohanad

Muna

Dheyaa

...Show More Authors

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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(4)

(2)

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