It is a paradox that medical experimentation on individuals, whether patients or healthy volunteers, is now controlled by strict ethical guidelines, while no such protection exists for whole populations which are subjected to medical interventions in the name of preventive medicine or health promotion. As many such interventions are either of dubious benefit or of uncertain harm-benefit balance, such as mass screening for cancers or for risk factors associated with coronary heart disease, there is no justification for maintaining the ethical (...) vacuum in which preventive medicine finds itself at present. (shrink)

Book reviewed in this article: Follies and Fallacies in Medicine. By Petr Skrabanek and James McCormick.

We present a pocket-size densely connected convolutional network (DenseNet) directed to classification of size-normalized colour images according to varieties of grapes captured in those images. We compare the DenseNet with three established small-size networks in terms of performance, inference time and model size. We propose a data augmentation that we use in training the networks. We train and evaluate the networks on in-field images. The trained networks distinguish between seven grapevine varieties and background, where four and three varieties, respectively, are (...) of red and green grapes. Compared to the established networks, the DenseNet is characterized by near state-of-the-art performance, short inference time and minimal model size. All these aspects qualify the network for real-time, mobile and edge computing applications. The DenseNet opens possibilities for constructing affordable selective harvesters in accordance with agriculture 4.0. (shrink)