International Journal for Research in Applied Science & Engineering Technology (IJRASET)

ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.538

Volume 11 Issue IV Apr 2023- Available at www.ijraset.com were solved using the regulation techniques. In other words, if the datasets have fewer images, then the algorithm needs to be designed with a regulation approach, which is known as data augmentation. Moreover, the attained accuracy by various methods is shown in Table 5.

However, the investigated approaches have many limitations like less accuracy, high false detection rate, high time utilization, and less performance [112, 113, 114]. Therefore, these limitations should be minimized to attain better output with high performance. In the future, DL with hybrid optimization methods can help to improve the image processing process and to enhance efficiency while reducing the fault detection rate.

ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.538

Volume 11 Issue IV Apr 2023- Available at www.ijraset.com

Already many approaches are available with the combination of DL and ML optimization, but still, it has recorded poor performance in some cases because of algorithm weakness. Hence, the hybridization of the algorithm can compensate the one weakness parameter with another optimization algorithm. Hereafter, it has applied a DL dense layer that will yield the finest performance compared to other models.

V. CONCLUSION

Image processing by ML has a major contribution for image segmentation, pre-processing, enhancement, restoration etc. Here, STARE, DRIVE, ROSE, BRATS, and ImageNet datasets were used to pattern images. Moreover, the importance of image processing by ML approaches is discussed. Various methods available for image processing and the techniques applied to each method were also analyzed. The execution rate of these approaches is analyzed regarding sensitivity, specificity, and accuracy. The study carried out the image processing and ML techniques following supervised and unsupervised methods proved to have a good performance. Also, the public dataset has provided a good comparison for the fundus images, as it contains more images. So, in the future, a hybrid optimized DL method incorporated with the Public dataset is better for standard research; it will provide better image processing, segmentation, pre-processing, and enhancement. Moreover, the use of a public dataset helps to improve the image processing methods and reduces the image complexities.

A. Acknowledgement

None

B. Compliance with Ethical Standards

1) Disclosure of Potential Conflict of Interest:

The authors declare that they have no potential conflict of interest.

2) Statement of Animal and Human Rights

3) Ethical Approval

All applicable institutional and/or national guidelines for the care and use of animals were followed.

4) Informed Consent

For this type of analysis formal consent is not needed.

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