Synthesis of photo- and ionochromic N-acylated 2-(aminomethylene)benzo[]thiophene-3(2)-ones with a terminal phenanthroline group.

A series of novel photo- and ionochromic N-acylated 2-(aminomethylene)benzo[]thiophene-3(2)-ones with a terminal phenanthroline receptor substituent was synthesized. Upon irradiation in acetonitrile or DMSO with light of 436 nm, they underwent - isomerization of the C=C bond, followed by very fast N→O migration of the acyl group and the formation of nonemissive O-acylated isomers. These isomers were isolated preparatively and fully characterized by IR, H, and C NMR spectroscopy as well as HRMS and XRD methods.

DocChip: A Configurable Hardware Accelerator for an End-to-End Historical Document Image Processing.

In recent years, there has been an increasing demand to digitize and electronically access historical records. Optical character recognition (OCR) is typically applied to scanned historical archives to transcribe them from document images into machine-readable texts. Many libraries offer special stationary equipment for scanning historical documents.

Synthesis and highly efficient light-induced rearrangements of diphenylmethylene(2-benzo[]thienyl)fulgides and fulgimides.

2-Benzo[]thienyl fulgides and fulgimides containing bulky diphenylmethylene substituents were synthesized in the form of their ring-opened - or isomers. In contrast to the majority of known fulgides/fulgimides, that form colored ring-closed structures under UV irradiation, the obtained compounds undergo an irreversible transformation leading to decoloration of their solutions. This rearrangement with the formation of the dihydronaphthalene core appeared to be by 2-3 orders of magnitude more efficient than for the known diphenylmethylene(aryl(hetaryl))fulgides.

Real-Time Energy Efficient Hand Pose Estimation: A Case Study.

The estimation of human hand pose has become the basis for many vital applications where the user depends mainly on the hand pose as a system input. Virtual reality (VR) headset, shadow dexterous hand and in-air signature verification are a few examples of applications that require to track the hand movements in real-time. The state-of-the-art 3D hand pose estimation methods are based on the Convolutional Neural Network (CNN).