- 标题
- 摘要
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- 实验方案
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Computer-Assisted Diagnosis for Diabetic Retinopathy Based on Fundus Images Using Deep Convolutional Neural Network
摘要： Diabetic retinopathy (DR) is a complication of long-standing diabetes, which is hard to detect in its early stage because it only shows a few symptoms. Nowadays, the diagnosis of DR usually requires taking digital fundus images, as well as images using optical coherence tomography (OCT). Since OCT equipment is very expensive, it will benefit both the patients and the ophthalmologists if an accurate diagnosis can be made, based solely on reading digital fundus images. In the paper, we present a novel algorithm based on deep convolutional neural network (DCNN). Unlike the traditional DCNN approach, we replace the commonly used max-pooling layers with fractional max-pooling. Two of these DCNNs with a different number of layers are trained to derive more discriminative features for classification. After combining features from metadata of the image and DCNNs, we train a support vector machine (SVM) classifier to learn the underlying boundary of distributions of each class. For the experiments, we used the publicly available DR detection database provided by Kaggle. We used 34,124 training images and 1,000 validation images to build our model and tested with 53,572 testing images. The proposed DR classifier classifies the stages of DR into five categories, labeled with an integer ranging between zero and four. The experimental results show that the proposed method can achieve a recognition rate up to 86.17%, which is higher than previously reported in the literature. In addition to designing a machine learning algorithm, we also develop an app called 'Deep Retina.' Equipped with a handheld ophthalmoscope, the average person can take fundus images by themselves and obtain an immediate result, calculated by our algorithm. It is beneficial for home care, remote medical care, and self-examination.
关键词： deep convolutional neural network,mobile app,fractional max-pooling,support vector machine,diabetic retinopathy,fundus images,teaching-learning-based optimization
更新于2025-09-23 15:23:52
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A new chaotic teaching learning based optimization for frequency reconfigurable antennas design
摘要： In this paper, a new chaotic teaching learning based optimization (CTLBO) is proposed. TLBO is a rather newly proposed population-based algorithm. This algorithm has no control parameters for the tuning and has a simple structure. We improve its performance by chaotic maps. First, the presented CTLBO is tested on nine unimodal/multimodal benchmark functions. Then, chaotic sequences are applied as vectors with different initial values for design of a frequency recon?gurable antenna (FRA) as a practical example. Comparisons of the performance of this algorithm with those of the basic TLBO, genetic algorithm and particle swarm optimization show the ability of this algorithm in design of FRAs in terms of faster convergence and better performance. A prototype of the optimized antenna with CTLBO algorithm is fabricated and the simulation and measurement results agree suitably.
关键词： Frequency recon?gurable antenna,Chaos theory,Teaching learning based optimization
更新于2025-09-19 17:15:36
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Insertion of Photovoltaic Solar Systems in Technological Education Institutions in Brazil: Teacher Perceptions Concerning Contributions towards Sustainable Development
摘要： Teaching spaces are seen as institutions presenting relevant power to promote sustainability. Thus, in addition to knowledge (re)producers, they must also assume ethical obligations to incorporate daily sustainability-oriented actions. In this context, this study evaluates faculty perceptions regarding contributions to the teaching–learning process and the di?usion of a pedagogical practice adhering to sustainability assumptions, arising from the insertion of photovoltaic solar systems in educational institutions. A study was conducted at the Rio Grande do Norte Federal Institute of Education Science and Technology, with 2.2 photovoltaic MWp distributed throughout its 21 campuses. This study investigated teacher knowledge and attitudes towards renewable energy sources in their school practice, as a way of understanding these issues and presenting propositions that will strengthen their role in daily school life. Teachers are aware of the importance of these sources, but their knowledge does not form links with their practice. Thus, the necessary connections to promote sustainability from the existence of institutional photovoltaic systems were proven insu?cient. They did not support the concept, nor the adoption of pedagogical practices linked to this technology. In addition, teacher inability to bring knowledge related to renewable energies to the classroom and link them to daily student lives was also noted. The adoption of renewable energy to promote a sustainability culture demands the formation of teacher knowledge and attitudes, and this training must follow a continuous path.
关键词： sustainability,photovoltaic,teaching–learning,renewable energy,sustainable development,education,school,teachers
更新于2025-09-19 17:13:59