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Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k dataset demonstrate superior performance compared to traditional methods, achieving higher accuracy, faster processing speed, and improved boundary preservation. Novelty: The proposed model effectively combines deep learning with fusion techniques, enhancing matting quality while maintaining robustness across various environmental conditions. Implications: These findings highlight the potential of integrating fusion techniques with deep learning for image matting, offering valuable insights for future research in automated image processing applications, including augmented reality, gaming, and interactive video technologies. Highlights:   Better Precision: Fusion techniques enhance fine detail preservation. Faster Processing: Lightweight U-Net improves speed and accuracy. Wide Applications: Useful for AR, gaming, and video processing.   Keywords: Deep image matting, computer vision, deep learning, fusion techniques, U-Net

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Publication Date
Fri Apr 20 2018
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Optimization of Digital Histopathology Image Quality
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One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues

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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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Publication Date
Mon Jan 02 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Image encryption technique using Lagrange interpolation
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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Image Hiding Using Discrete Cosine Transform
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Steganography is a mean of hiding information within a more obvious form of
communication. It exploits the use of host data to hide a piece of information in such a way
that it is imperceptible to human observer. The major goals of effective Steganography are
High Embedding Capacity, Imperceptibility and Robustness. This paper introduces a scheme
for hiding secret images that could be as much as 25% of the host image data. The proposed
algorithm uses orthogonal discrete cosine transform for host image. A scaling factor (a) in
frequency domain controls the quality of the stego images. Experimented results of secret
image recovery after applying JPEG coding to the stego-images are included.

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Publication Date
Mon Jan 01 2007
Journal Name
2007 Ieee International Conference On Signal Processing And Communications
Fast Multi-level Image Vector Quantization
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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Image Zooming Using Inverse Slantlet Transform
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Digital image is widely used in computer applications. This paper introduces a proposed method of image zooming based upon inverse slantlet transform and image scaling. Slantlet transform (SLT) is based on the principle of designing different filters for different scales.

      First we apply SLT on color image, the idea of transform color image into slant, where large coefficients are mainly the   signal and smaller one represent the noise. By suitably modifying these coefficients , using scaling up image by  box and Bartlett filters so that the image scales up to 2X2 and then inverse slantlet transform from modifying coefficients using to the reconstructed image .

  &nbs

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
Image Reconstruction Using Modified Hybrid Transform
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In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.

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Publication Date
Tue Mar 08 2022
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Data Hiding in 3D-Medical Image
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Information hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Conformity and nonconformity and their relation to the emotional balance of high school students
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 Complex and complex psychological processes are complexand are the result of convergence, convergence and interaction between variables, including the subject of mediation or group or individual and psychological processes involved in the variance, including - personal knowledge and emotional tone (Osman, 1987, p. 8 ). An emotionally balanced individual has the ability to endure and delay meeting needs and has the ability to endure as much as possible. Of the emotional balance of the individual is characterized by emotional stability, show some signs of emotional agitation toward any kind of opposition, anger and realism in self-life and discipline (Swift, 1996, p. 44) Van, et al. , Indicates that people with low emotional balance,

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
The impact of learning strategies in the collection of biology and their systemic thinking
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Research Summary The aim of the search for knowledge of the effect generative learning strategy in: 1 - Achievement of the second grade. 2 - Systemic thinking for the second grade students when studying the biology. The study sample increased (60) students distributed into two equal experimental and control groups. Prepare the test of 40 pieces of multiple choice type and prepare a test for systematic thinking according to three skills 1. Understand the relationships between the parts of the systemic form and complement the sentences given 2 - complement the relationships between parts of the systemic form 3. Building the systemic form. It was a search result 1- There is a difference of statistical significance (at level 0.05) between th

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