Current status of the international Halley Watch infrared net archive

The primary purposes of the Halley Watch have been to promote Halley observations, coordinate and standardize the observing where useful, and to archive the results in a database readily accessible to cometary scientists. The intention of IHW is to store the observations themselves, along with any information necessary to allow users to understand and use the data, but to exclude interpretations of these data. Each of the archives produced by the IHW will appear in two versions: a printed archive and a digital archive on CD-ROMs. The archive is expected to have a very long lifetime. The IHW has already produced an archive for P/Crommelin. This consists of one printed volume and two 1600 bpi tapes. The Halley archive will contain at least twenty gigabytes of information

Wittgensteins Beziehungen zum Schlick-Kreis

Gilt es von uns oder gilt es von Wittgenstein, daß es uns bei vielen der Probleme, die aufscheinen, wenn wir sein Leben und sein Werk betrachten, schwierig erscheint, nicht unter dem einen oder anderen Gesichtspunkt zu viel zu sagen, ihn oder andere nicht überheblich zu behandeln, nicht zu verteidigen, und in Auseinandersetzungen, welche Gefahr laufen, entweder irreal oder anachronistisch zu sein, nicht für jemanden Partei zu ergreifen? Ich denke hier zum Beispiel an sein Judentum, an seine Beziehungen zu Russell und besonders an das vorliegende Thema; dem Leser werden leicht andere Beispiele einfallen. Wie schon angedeutet, es ist vielleicht sogar meine einleitende Frage eine falsche Fragestellung (wie es sicherlich einige der Auseinandersetzungen sind). In Wirklichkeit ist das Problem unsere historische Beziehung zu Wittgenstein und zu den aufgeworfenen Fragen; man kann sich vorstellen, daß künftige oder jüngere Generationen besser imstande sein werden zu sagen, wie es eigentlich gewesen ist, obwohl manche Themen ― und vielleicht fällt Wittgenstein darunter ― die neutrale Haltung des Historikers besonders zu belasten scheinen. Daß der Mangel an Übereinstimmung und der Widerstand gegen Stereotype sowohl eine ungereimte und unannehmbare Seite, als auch eine belebende und befreiende Funktion haben kann, scheint eine Wahrheit zu sein, die sich von selbst versteht; aber es ist nicht leicht, sie zu akzeptieren. Es ist ohne Zweifel nutzlos zu fragen, wie zeitgebunden diese Wirkung ist

A Tapestry: Susan Edwards-McKie Interviews Professor Dr B. F. McGuinness on the Occasion of His 90th Birthday

Susan Edwards-McKie interviews Professor Dr B. F. McGuinness on the occasion of his 90th birthday

Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation

Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk production. By accurately estimating herbage mass and composition, targeted nitrogen fertiliser application strategies can be deployed to improve localised regions in a herbage field, effectively reducing the negative impacts of over-fertilization on biodiversity and the environment. In this context, deep learning algorithms offer a tempting alternative to the usual means of sward composition estimation, which involves the destructive process of cutting a sample from the herbage field and sorting by hand all plant species in the herbage. The process is labour intensive and time consuming and so not utilised by farmers. Deep learning has been successfully applied in this context on images collected by high-resolution cameras on the ground. Moving the deep learning solution to drone imaging, however, has the potential to further improve the herbage mass yield and composition estimation task by extending the ground-level estimation to the large surfaces occupied by fields/paddocks. Drone images come at the cost of lower resolution views of the fields taken from a high altitude and requires further herbage ground-truth collection from the large surfaces covered by drone images. This paper proposes to transfer knowledge learned on ground-level images to raw drone images in an unsupervised manner. To do so, we use unpaired image style translation to enhance the resolution of drone images by a factor of eight and modify them to appear closer to their ground-level counterparts. We then ... ~\url{www.github.com/PaulAlbert31/Clover_SSL}.Comment: 11 pages, 5 figures. Accepted at the Agriculture-Vision CVPR 2022 Worksho

Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation

Sward species composition estimation is a tedious one. Herbage must be collected in the field, manually separated into components, dried and weighed to estimate species composition. Deep learning approaches using neural networks have been used in previous work to propose faster and more cost efficient alternatives to this process by estimating the biomass information from a picture of an area of pasture alone. Deep learning approaches have, however, struggled to generalize to distant geographical locations and necessitated further data collection to retrain and perform optimally in different climates. In this work, we enhance the deep learning solution by reducing the need for ground-truthed (GT) images when training the neural network. We demonstrate how unsupervised contrastive learning can be used in the sward composition prediction problem and compare with the state-of-the-art on the publicly available GrassClover dataset collected in Denmark as well as a more recent dataset from Ireland where we tackle herbage mass and height estimation.Comment: 3 pages. Accepted at the 29th EGF General Meeting 202