Recently, image inpainting has been proposed as a solution for restoring the polluted image in the field of computer vision. Further, face inpainting is a subfield of image inpainting, which refers to a set of image e...
详细信息
This article introduces a novel algorithm, named 'CrowdDC,' that aims to solve the issue of ranking large datasets based on subjective factors using crowdsourced paired comparisons. In traditional paired compa...
详细信息
Breast cancer poses a threat to women’s health and contributes to an increase in mortality rates. Mammography has proven to be an effective tool for the early detection of breast cancer. However, it faces many challe...
详细信息
Breast cancer poses a threat to women’s health and contributes to an increase in mortality rates. Mammography has proven to be an effective tool for the early detection of breast cancer. However, it faces many challenges in early breast cancer detection due to poor image quality, traditional segmentation, and feature extraction. Therefore, this work addresses these issues and proposes an attention-based backpropagation convolutional neural network (ABB-CNN) to detect breast cancer from mammogram images more accurately. The proposed work includes image enhancement, reinforcement learning-based semantic segmentation (RLSS), and multiview feature extraction and classification. The image enhancement is performed by removing noise and artefacts through a hybrid filter (HF), image scaling through a pixel-based bilinear interpolation (PBI), and contrast enhancement through an election-based optimization (EO) algorithm. In addition, the RLSS introduces intelligent segmentation by utilizing a deep Q network (DQN) to segment the region of interest (ROI) strategically. Moreover, the proposed ABB-CNN facilitates multiview feature extraction from the segmented region to classify the mammograms into normal, malignant, and benign classes. The proposed framework is evaluated on the collected and the digital database for screening mammography (DDSM) datasets. The proposed framework provides better outcomes in terms of accuracy, sensitivity, specificity, precision, f-measure, false-negative rate (FNR) and area under the curve (AUC). This work achieved (99.20%, 99.35%), (99.56%, 99.66%), (98.96%, 98.99%), (99.05%, 99.12%), (0.44%, 0.34%), (99.31%, 99.39%) and (99.27%, 99.32%) of accuracy, sensitivity, specificity, precision, FNR, f-measure and AUC on (collected, DDSM datasets), respectively. This research addresses the prevalent challenges in breast cancer identification and offers a robust and highly accurate solution by integrating advanced deep-learning techniques. The evaluated re
The cellular automaton (CA), a discrete model, is gaining popularity in simulations and scientific exploration across various domains, including cryptography, error-correcting codes, VLSI design and test pattern gener...
详细信息
Animation is a widespread artistic expression that holds a special place in people's hearts. Traditionally, animation creation has relied heavily on manual techniques, demanding skilled drawing abilities and a sig...
详细信息
Owing to the variety of ways to view the Internet and the changes in user behavior on the Internet, network traffic has been explosively growing in recent years. Users can watch high-quality videos on the Internet;it ...
详细信息
The overgeneralisation may happen because most studies on data publishing for multiple sensitive attributes(SAs)have not considered the personalised privacy ***,sensitive information disclosure may also be caused by t...
详细信息
The overgeneralisation may happen because most studies on data publishing for multiple sensitive attributes(SAs)have not considered the personalised privacy ***,sensitive information disclosure may also be caused by these personalised *** address the matter,this article develops a personalised data publishing method for multiple *** to the requirements of individuals,the new method partitions SAs values into two categories:private values and public values,and breaks the association between them for privacy *** the private values,this paper takes the process of anonymisation,while the public values are released without this *** algorithm is designed to achieve the privacy mode,where the selectivity is determined by the sensitive value frequency and undesirable *** experimental results show that the proposed method can provide more information utility when compared with previous *** theoretic analyses and experiments also indicate that the privacy can be guaranteed even though the public values are known to an *** overgeneralisation and privacy breach caused by the personalised requirement can be avoided by the new method.
If the video has long been mentioned as a widespread visualization form, the animation sequence in the video is mentioned as storytelling for people. Producing an animation requires intensive human labor from skilled ...
详细信息
This article addresses the scheduling problem of coflows in identical parallel networks, a well-known NPNP-hard problem. We consider both flow-level scheduling and coflow-level scheduling problems. In the flow-level s...
详细信息
Heart disease increases the strain on the heart by reducing its ability to pump blood throughout the body, which can lead to heart attacks and strokes. Heart disease is becoming a global threat to the world due to peo...
详细信息
暂无评论