Si-based integrated circuits have been intensively developed over the past several decades through ultimate device scaling. However, the Si technology has reached the physical limitations of the scaling. These limitations have fuelled the search for alternative active materials (for transistors) and the introduction of optical interconnects (called “Si photonics”). A series of attempts to circumvent the Si technology limits are based on the use of III-V compound semiconductor due to their superior benefits, such as high electron mobility and direct bandgap. To use their physical properties on a Si platform, the formation of high-quality III-V films on the Si (III-V/Si) is the basic technology ; however, implementing this technology using a high-throughput process is not easy. Here, we report new concepts for an ultra-high-throughput heterogeneous integration of high-quality III-V films on the Si using the wafer bonding and epitaxial lift off (ELO) technique. We describe the ultra-fast ELO and also the re-use of the III-V donor wafer after III-V/Si formation. These approaches provide an ultra-high-throughput fabrication of III-V/Si substrates with a high-quality film, which leads to a dramatic cost reduction. As proof-of-concept devices, this paper demonstrates GaAs-based high electron mobility transistors (HEMTs), solar cells, and hetero-junction phototransistors on Si substrates.
The effects of epitaxial materials and solar cell design on the performance of solar cells grown by the multilayer approach are investigated. The novel solar cell structure with a p‐on‐n type configuration suggested exhibits improved uniformity in the photovoltaic performance because of the suppression of Zn diffusion. This approach provides routes to achieve further improvements and acts as a guideline for the commercialization of the multilayer technique.
Purpose
This study aims to provide an automatic strabismus screening method for people who live in remote areas with poor medical accessibility.
Materials and methods
The proposed method first utilizes a pretrained convolutional neural network-based face-detection model and a detector for 68 facial landmarks to extract the eye region for a frontal facial image. Second, Otsu’s binarization and the HSV color model are applied to the image to eliminate the influence of eyelashes and canthi. Then, the method samples all of the pixel points on the limbus and applies the least square method to obtain the coordinate of the pupil center. Lastly, we calculated the distances from the pupil center to the medial and lateral canthus to measure the deviation of the positional similarity of two eyes for strabismus screening.
Result
We used a total of 60 frontal facial images (30 strabismus images, 30 normal images) to validate the proposed method. The average value of the iris positional similarity of normal images was smaller than one of the strabismus images via the method (p-value<0.001). The sample mean and sample standard deviation of the positional similarity of the normal and strabismus images were 1.073 ± 0.014 and 0.039, as well as 1.924 ± 0.169 and 0.472, respectively.
Conclusion
The experimental results of 60 images show that the proposed method is a promising automatic strabismus screening method for people living in remote areas with poor medical accessibility.
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