A GAN-based genetic algorithm for solving the 3D bin packing problem.

The 3D bin packing problem is a challenging combinatorial optimization problem with numerous real-world applications. In this paper, we present a novel approach for solving this problem by integrating a generative adversarial network (GAN) with a genetic algorithm (GA). Our proposed GAN-based GA utilizes the GAN to generate high-quality solutions and improve the exploration and exploitation capabilities of the GA.

Image projective transformation rectification with synthetic data for smartphone-captured chest X-ray photos classification.

Automatic interpretation of chest X-ray (CXR) photos taken by smartphones at the same performance level as with digital CXRs is challenging, due to the projective transformation caused by the non-ideal camera position. Existing rectification methods for other camera-captured photos (document photos, license plate photos, etc.) cannot precisely rectify the projective transformation of CXR photos, due to its specific projective transformation type.

DMNet: A Personalized Risk Assessment Framework for Elderly People With Type 2 Diabetes.

Type 2 diabetes is the most common chronic disease for the elderly people. This disease is difficult to be cured and causes continued medical expenses. The early and personalized risk assessment of type 2 diabetes is necessary.

DeSeg: auto detector-based segmentation for brain metastases.

Delineation of brain metastases (BMs) is a paramount step in stereotactic radiosurgery treatment. Clinical practice has specific expectation on BM auto-delineation that the method is supposed to avoid missing of small lesions and yield accurate contours for large lesions. In this study, we propose a novel coarse-to-fine framework, named detector-based segmentation (DeSeg), to incorporate object-level detection into pixel-wise segmentation so as to meet the clinical demand.