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A Survey on Image Caption Generation in Various Languages
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      The image caption is the process of adding an explicit, coherent description to the contents of the image. This is done by using the latest deep learning techniques, which include computer vision and natural language processing, to understand the contents of the image and give it an appropriate caption. Multiple datasets suitable for many applications have been proposed. The biggest challenge for researchers with natural language processing is that the datasets are incompatible with all languages. The researchers worked on translating the most famous English data sets with Google Translate to understand the content of the images in their mother tongue. In this paper, the proposed review aims to enhance the understanding of image captioning strategies and to survey previous research related to image captioning while examining the most popular databases in different languages, mostly English, translating into other languages using the latest models for describing images, summarizing evaluation measures, and comparing them.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Software & Hardware Research In Engineering
Frontal Facial Image Compression of Hybrid Base
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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Color Image Compression of Inter-Prediction Base
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Publication Date
Mon Nov 29 2021
Journal Name
Iraqi Journal Of Science
Comparing the Main Approaches of Image Segmentation
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Images are important medium for conveying information; this makes improvement of image processing techniques also important. Interpretation of image content is one of the objectives of image processing techniques. Image interpretation that segments the image to number of objects called image segmentation. Image segmentation is an important field to deal with the contents of images and get non overlapping regions coherent in texture and color, it is important to deal only with objects with significant information. This paper presents survey of the most commonly used approaches of image segmentation and the results of those approaches have been compared and according to the measurement of quality presented in this paper the Otsu's threshol

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Publication Date
Wed Jul 25 2018
Journal Name
International Journal Of Engineering Trends And Technology
Fixed Predictor Polynomial Coding for Image Compression
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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
Visible image watermarking using biorthogonal wavelet transform
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In this paper, visible image watermarking algorithm based on biorthogonal wavelet
transform is proposed. The watermark (logo) of type binary image can be embedded in the
host gray image by using coefficients bands of the transformed host image by biorthogonal
transform domain. The logo image can be embedded in the top-left corner or spread over the
whole host image. A scaling value (α) in the frequency domain is introduced to control the
perception of the watermarked image. Experimental results show that this watermark
algorithm gives visible logo with and no losses in the recovery process of the original image,
the calculated PSNR values support that. Good robustness against attempt to remove the
watermark was s

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Publication Date
Thu Oct 25 2018
Journal Name
Al–bahith Al–a'alami
Image of relief organizations for displaced Iraqis
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This research aims to know the intellectual picture the displaced people formed about aid organizations and determine whether they were positive or negative, the researchers used survey tool as standard to study the society represented by displaced people living in Baghdad camps from Shiites, Sunnis, Shabak, Turkmen, Christians, and Ezidis.
The researcher reached to important results and the most important thing he found is that displaced people living in camps included in this survey hold a positive opinion about organizations working to meet their demands but they complain about the shortfall in the health care side.
The research also found that displaced people from (Shabak, Turkmen, and Ezidi) minorities see that internati

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Publication Date
Thu Aug 30 2018
Journal Name
Iraqi Journal Of Science
Analytical Study of Medical Image Combination Techniques
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Image combination is a technique that fuses two or more medical images taken with different conditions or imaging devices into a single image contain complete information. In this study relied on mathematical, statistical and spatial techniques, to fuse MRI images that captured horizontal and vertical times (T1, T2),  and applied a method of supervised classification based on the minimum distance before and after combination process, then examine the quality of the resulting image based on the statistical standards resulting from the analysis of edge analysis, showing the results to identify the best techniques adopted in combination process, determine the exact details in each class and between classes.

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Effective Digital Image Colors Reduction/Quantization Method
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In the current research work, a method to reduce the color levels of the pixels within digital images was proposed. The recent strategy was based on self organization map neural network method (SOM). The efficiency of recent method was compared with the well known logarithmic methods like Floyd-Steinberg (Halftone) dithering and Octtrees (Quadtrees) methods. Experimental results have shown that by adjusting the sampling factor can produce higher-quality images with no much longer run times, or some better quality with shorter running times than existing methods. This observation refutes the repeated neural networks is necessarily slow but have best results. The generated quantization map can be exploited for color image compression, clas

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression using Hierarchal Linear Polynomial Coding
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Publication Date
Fri Jul 18 2014
Journal Name
International Journal Of Computer Applications
3-Level Techniques Comparison based Image Recognition
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Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

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