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Here the authors investigated the optical possibilities of gelatin and acrylic in regards to potential implementations at soft contact lenses. They fabricated lenses of different shapes and evaluated the refraction of laser light finding that gelatin needed to be thickened or increased in curvature to account for its lower refractive index compared to plastics, or used in a mixture to strengthen the lens.

Semantic segmentation - labelling each pixel in an image to a specific class- models require large amounts of manually labeled and collected data to train.

In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.