Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading to blindness. Computer-Aided Diagnosis systems play an essential role in detecting features in fundus images. Fundus images may include blood vessels, exudates, micro-aneurysm, hemorrhages, and neovascularization. In this paper, our model combines automatic detection for the diabetic retinopathy classification with localization methods depending on weakly-supervised learning. The model has four stages; in stage one, various preprocessing techniques are applied to smooth the data set. In stage two, the network had gotten deeply to the optic disk segment for eliminating any exudate's false prediction because the exudates had the same color pixel as the optic disk. In stage three, the network is fed through training data to classify each label. Finally, the layers of the convolution neural network are re-edited, and used to localize the impact of DR on the patient's eye. The framework tackles the matching technique between two essential concepts where the classification problem depends on the supervised learning method. While the localization problem was obtained by the weakly supervised method. An additional layer known as weakly supervised sensitive heat map (WSSH) was added to detect the ROI of the lesion at a test accuracy of 98.65%, while comparing with Class Activation Map that involved weakly supervised technology achieved 0.954. The main purpose is to learn a representation that collect the central localization of discriminative features in a retina image. CNN-WSSH model is able to highlight decisive features in a single forward pass for getting the best detection of lesions.
The study aims to identify the metamemory and perceptual speed among College students, the correlation between metamemory and perceptual speed among College students, and to which extend does metamemory contribute to perceptual speed among College students. The sample consisted of group of students were selected randomly by the researcher from five-different disciplines at the college of education for pure sciences. To collect study data, the researcher utilized two scales: perceptual speed scale that has translated to Arabic language by (Al-Shraqawi, Al- Shaikh, and Nadia Abed Al-Salam (1993). The second scale is metamemory scale (2002) which has translated to Arabic by Abu Ghazal (2007). The results revealed that college students have
... Show MoreIt is the grace of God and his grace that he accepts repentance for his slaves, forgives their bad deeds in return for their misfortune, or offers them a good deed, but pardons many of them for free. Therefore, it is not long for God Almighty to forgive His mercy for many of His slaves and bring them to Paradise with no punishment or punishment, even if they have committed some sins, because of the multitude of their favorable navigational disadvantages, or even without gratitude thanks to him and him. With all this, some have overlooked the old and new on these things and amazed at the hadeeth ((God may have seen the people of the full moon and said do what you want, I have forgiven you)). Therefore, the scholars tried to answer some of
... Show MoreWriting in English is one of the essential factors for successful EFL learning .Iraqi students at the preparatory schools encounter problems when using their background knowledge in handling subskills of writing(Burhan,2013:164).Therefore, this study aims to investigate the 4thyear preparatory school students’ problems in English composition writing, and find solutions to these pro
... Show MoreWe use of multi-choice Goal Programming (MCGP), which is a developed model of Goal Programming where it is used in circumstances of the multiplicity and difference of goals when choosing between decision alternatives in cases of allocating resources, as it is a model that seeks to find the closest and best solutions to the specific values of the goals within the aspiration levels, as the first goal in the multi-choice goal programming model that is used to reduce the total cost of storage and shortage, while the other goal was to reduce the difference between the real demand that the hospitals need from the blood transfusion center and the units that already achieved. The case Iraqi Center
... Show More This study titled “digital addiction and its relationship to social isolation among children in the autism spectrum from the point of view of their parents” in which the
researcher addressed an important topic which is knowledge of digital addiction in a
child with autism spectrum and its relationship to social isolation in them.
The study aimed to dhed the light on the digital addiction in a spectrum child Autism
from the point of view of their parents، by knowing the extent of addiction of children
in the autism spectrum، and identifying the relationship between electronic addiction and the social isolation of children in the autism spectrum.The study presented
several hypotheses،
As the prices of the fuel and power had fluctuated many times in the last decade and new policies appeared and signed by most of the world countries to eliminate global warming and environmental impact on the earth surface and humanity exciting, an urgent need appeared to develop the renewable energy harnessing technologies on the short-term and long-term and one of these promising technologies are the vertical axis wind turbines, and mostly the combined types. The purpose of the present work is to combine a cavity type Savonius with straight bladed Darrieus to eliminate the poor self-starting ability for Darrieus type and low performance for Savonius type and for this purpose, a three-bladed Darrieus type with symmetric
... Show MoreThis study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi
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