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Entropyposting or the Art of Sabotaging Your Online Self

Inside the YouTube decade

What’s online video today, fifteen years into its exponential growth? In the age of the smart phone, video accompanies, informs, moves, and distracts us. What started off with amateur prosumers on YouTube has spread to virtually all communication apps: say it with moving images. Are you addicted yet? Look into that tiny camera, talk and move the phone, show us around, and prove the others out there that you exist!With this third reader the Video Vortex community — initiated in 2007 by the Instituteof Network Cultures — proves that it is still alive and kicking. No matter its changes, the network is still driven by its original mission to develop a critical vocabulary for this rapidly spreading visual culture: what are the specific characteristics of online video in terms of aesthetics and political economy of image production and distribution, and how do they compare to film and television? Who is the Andre Bazin of the YouTube age? Honestly, why can’t we name a single online video critic? Can we face the fact that hardly anyone is using the internet? What are you going to do with that 4K camera in your smartphone? Have we updated Marshall McLuhan’s hot and cold media for our digital era yet? Who dares? We see the Woman with a Smartphone Camera in action, but who will be our Vertov and lead the avant-garde? Who stops us? Let us radically confront the technological presence as it is and forget the pathetic regression to past formats: radical acceptance of the beautiful mess called the net.

The age of total images

In The Age of Total Images, art historian Ana Peraica focuses on the belief that the shape of the planet is two-dimensional which has been reawakened in the late 20th and early 21st centuries, and the ways in which these ‘flat Earth’ conspiracy theories are symptomatic of post-digital image culture. Such theories, proven to be false both in Antiquity and Modernity, but once held to be true in the Medieval Period, have influenced a return to a kind of ‘New Medievalism’.

I’M A.I. IMage Processing and Artificial Intelligence [Inaugurele rede]

Brochure from the Inauguration of Klaas Dijkstra, professor Computer Vision and Data Science

Performance Characterization of an Illumination-Based Low-Cost Multispectral Camera

Spectral imaging has many applications, from methane detection using satellites to disease detection on crops. However, spectral cameras remain a costly solution ranging from 10 thousand to 100 thousand euros for the hardware alone. Here, we present a low-cost multispectral camera (LC-MSC) with 64 LEDs in eight different colors and a monochrome camera with a hardware cost of 340 euros. Our prototype reproduces spectra accurately when compared to a reference spectrometer to within the spectral width of the LEDs used and the ±1σ variation over the surface of ceramic reference tiles. The mean absolute difference in reflectance is an overestimate of 0.03 for the LC-MSC as compared to a spectrometer, due to the spectral shape of the tiles. In environmental light levels of 0.5 W m−2 (bright artificial indoor lighting) our approach shows an increase in noise, but still faithfully reproduces discrete reflectance spectra over 400 nm–1000 nm. Our approach is limited in its application by LED bandwidth and availability of specific LED wavelengths. However, unlike with conventional spectral cameras, the pixel pitch of the camera itself is not limited, providing higher image resolution than typical high-end multi- and hyperspectral cameras. For sample conditions where LED illumination bands provide suitable spectral information, our LC-MSC is an interesting low-cost alternative approach to spectral imaging.

Hyper-spectral frequency selection for the classification of vegetation diseases

Reducing the use of pesticides by early visual detection of diseases in precision agriculture is important. Because of the color similarity between potato-plant diseases, narrow band hyper-spectral imaging is required. Payload constraints on unmanned aerial vehicles require reduc- tion of spectral bands. Therefore, we present a methodology for per-patch classification combined with hyper-spectral band selection. In controlled experiments performed on a set of individual leaves, we measure the performance of five classifiers and three dimensionality-reduction methods with three patch sizes. With the best-performing classifier an error rate of 1.5% is achieved for distinguishing two important potato-plant diseases.