Nechirvan Asaad Zebari's research while affiliated with Duhok Polytechnic University and other places

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Publications (3)

Skin Lesion Segmentation Using K-means Clustering with Removal Unwanted RegionsSkin Lesion Segmentation Using K-means Clustering with Removal Unwanted Regions
Article
  • Dec 2022
The segmentation of skin lesions is crucial to the early and accurate identification of skin cancer by computerized systems. It is difficult to automatically divide skin lesions in dermoscopic images because of challenges such as hairs, gel bubbles, ruler marks, fuzzy boundaries, and low contrast. We proposed an effective method based on K-means an...
Figure 1. Proposed automated breast cancer recognition model.
Figure 3. Multi-fractal fusion model based on blocks.
Distribution of used benign and malignant mammogram images.
Mammogram denoising results based on EWBFEM.
+8 First experiment of mammogram classification results as benign or...
Breast Cancer Detection Using Mammogram Images with Improved Multi-Fractal Dimension Approach and Feature Fusion
Article
Full-text available
  • Dec 2021
Breast cancer detection using mammogram images at an early stage is an important step in disease diagnostics. We propose a new method for the classification of benign or malignant breast cancer from mammogram images. Hybrid thresholding and the machine learning method are used to derive the region of interest (ROI). The derived ROI is then separate...
Fig 2: General Process of Steganography [12]
Fig 3: Bock Diagram of Steganography Application
Fig4: Steganography Mechanism Using Swarm Algorithms
Fig 5: The Behavious of Ant Colony
Fig 6: The General Concept of Firefly Algorithm
Image Steganography Based on Swarm Intelligence Algorithms: A Survey
Article
Full-text available
  • Jun 2020
Information security and confidentiality are the prime concern of any type of communication. The techniques that utilizing inconspicuous digital media such as text, audio, video and image for hiding confidential data in it are collectively called Steganography. The key challenge of steganographic system design is to maintain a fair trade-off betwee...

Citations

... Deep ANNs are ANNs having multiple layers between the input and output layer (also known as hidden layers), and training such networks is referred to as deep learning. Typically, supervised learning is used for training, which involves manually annotating the data before to training and using backpropagation to change the weights for each input [16]. ...
Reference: A Survey on Using Machine Learning and Deep Learning based Iris Recognition
... Histogram reveals each pixel's precise occurrence in the picture. The remarkable resemblance between the histograms of the host and the stego shows the minimum distortion after the secret picture has been integrated into the host image [13]. ...
Reference: Data Hiding by Unsupervised Machine Learning Using Clustering K-mean Technique