arXiv subjects

Norah Asiri

Publications and source records attributed to Norah Asiri.

4 recordsLinked to original sources

arXiv2025

A Deep Learning-Based Unified Framework for Red Lesions Detection on Retinal Fundus Images

Red-lesions, microaneurysms (MAs) and hemorrhages (HMs), are the early signs of diabetic retinopathy (DR). The automatic detection of MAs and HMs on retinal fundus images is a challenging task. Most of the existing methods detect either only MAs or only HMs because of the difference in their texture, sizes, and morphology. Though some methods detect both MAs and HMs, they suffer from the curse of dimensionality of shape and colors features and fail to detect all shape variations of HMs such as flame-shaped. Leveraging the progress in deep learning, we proposed a two-stream red lesions detection system dealing simultaneously with small and large red lesions. For this system, we introduced a new ROIs candidates generation method for large red lesions on fundus images; it is based on blood vessel segmentation and morphological operations, and reduces the computational complexity, and enhances the detection accuracy by generating a small number of potential candidates. For detection, we proposed a framework with two streams. We used pretrained VGGNet as a backbone model and carried out several extensive experiments to tune it for vessels segmentation and candidates generation, and finally learning the appropriate mapping, which yields better detection of the red lesions comparing with the state-of-the-art methods. The experimental results validated the effectiveness of the system in the detection of both MAs and HMs; it yields higher performance for per lesion detection; its sensitivity equals 0.8589 and good FROC score under 8 FPIs on DiaretDB1-MA reports FROC=0.7518, and with SN=0.7552 and good FROC score under 2,4and 8 FPIs on DiaretDB1-HM, and SN=0.8157 on e-ophtha with overall FROC=0.4537 and on ROCh dataset with FROC=0.3461 which is higher than the state-of-the art methods. For DR screening, the system performs well with good AUC on DiaretDB1-MA, DiaretDB1-HM, and e-ophtha datasets.

eess.IV↗

arXiv2024

Security and Privacy Issues in Cloud Storage

Even with the vast potential that cloud computing has, so far, it has not been adopted by the consumers with the enthusiasm and pace that it be worthy; this is a very reason statement why consumers still hesitated of using cloud computing for their sensitive data and the threats that prevent the consumers from shifting to use cloud computing in general and cloud storage in particular. The cloud computing inherits the traditional potential security and privacy threats besides its own issues due to its unique structures. Some threats related to cloud computing are the insider malicious attacks from the employees that even sometime the provider unconscious about, the lack of transparency of agreement between consumer and provider, data loss, traffic hijacking, shared technology and insecure application interface. Such threats need remedies to make the consumer use its features in secure way. In this review, we spot the light on the most security and privacy issues which can be attributed as gaps that sometimes the consumers or even the enterprises are not aware of. We also define the parties that involve in scenario of cloud computing that also may attack the entire cloud systems. We also show the consequences of these threats.

cs.CR↗

arXiv2022

Non-recursive Approach for Sort-Merge Join Operation

Several algorithms have been developed over the years to perform join operation which is executed frequently and affects the efficiency of the database system. Some of these efforts prove that join performance mainly depends on the sequences of execution of relations in addition to the hardware architecture. In this paper, we present a method that processes a many-to-many multi join operation by using a non-recursive reverse polish notation tree for sort-merge join. Precisely, this paper sheds more light on main memory join operation of two types of sort-merge join sequences: sequential join sequences (linear tree) and general join sequences (wide bushy tree, also known as composite inner) and also tests their performance and functionality. We will also provide the algorithm of the proposed system that shows the implementation steps.

cs.DB↗

arXiv2019

Deep Learning based Computer-Aided Diagnosis Systems for Diabetic Retinopathy: A Survey

Diabetic retinopathy (DR) results in vision loss if not treated early. A computer-aided diagnosis (CAD) system based on retinal fundus images is an efficient and effective method for early DR diagnosis and assisting experts. A computer-aided diagnosis (CAD) system involves various stages like detection, segmentation and classification of lesions in fundus images. Many traditional machine-learning (ML) techniques based on hand-engineered features have been introduced. The recent emergence of deep learning (DL) and its decisive victory over traditional ML methods for various applications motivated the researchers to employ it for DR diagnosis, and many deep-learning-based methods have been introduced. In this paper, we review these methods, highlighting their pros and cons. In addition, we point out the challenges to be addressed in designing and learning about efficient, effective and robust deep-learning algorithms for various problems in DR diagnosis and draw attention to directions for future research.

cs.CV↗