Equirectangular Image Data Detection, Segmentation and Classification of Varying Sized Traffic Signs: A Comparison of Deep Learning Methods.

There are known limitations in mobile omnidirectional camera systems with an equirectangular projection in the wild, such as momentum-caused object distortion within images, partial occlusion and the effects of environmental settings. The localization, instance segmentation and classification of traffic signs from image data is of significant importance to applications such as Traffic Sign Detection and Recognition (TSDR) and Advanced Driver Assistance Systems (ADAS). Works show the efficacy of using state-of-the-art deep pixel-wise methods for this task yet rely on the input of classical landscape image data, automatic camera focus and collection in ideal weather settings, which does not accurately represent the application of technologies in the wild.

Genome Sequences of 14 Siphophages That Infect Serratia marcescens.

We announce the complete genome sequences of 14 bacteriophages isolated from wastewater treatment plants. These phages define two previously undescribed types which we call the Carrot-like phage cluster (phages Carrot, BigDog, LittleDog, Niamh, Opt-148, Opt-169, PhooPhighters, Rovert, Serratianator, Stoker, Swain, and Ulliraptor) and Tlacuache-like phage cluster (Tlacuache and Opt-155).