Previous approaches for scene text detection have already achieved promising performances across various benchmarks. However, they usually fall short when dealing with challenging scenarios, even when equipped with deep neural network models, because the overall performance is determined by the interplay of multiple stages and components in the pipelines. In this work, we propose a simple yet powerful pipeline that yields fast and accurate text detection in natural scenes. The pipeline directly predicts words or text lines of arbitrary orientations and quadrilateral shapes in full images, eliminating unnecessary intermediate steps (e.g., candidate aggregation and word partitioning), with a single neural network. The simplicity of our pipeline allows concentrating efforts on designing loss functions and neural network architecture. Experiments on standard datasets including ICDAR 2015, COCO-Text and MSRA-TD500 demonstrate that the proposed algorithm significantly outperforms state-of-the-art methods in terms of both accuracy and efficiency. On the ICDAR 2015 dataset, the proposed algorithm achieves an F-score of 0.7820 at 13.2fps at 720p resolution.

There is an ongoing debate about the fundamental security of existing quantum key exchange schemes. This debate indicates not only that there is a problem with security but also that the meanings of perfect, imperfect, conditional and unconditional (information theoretic) security in physically secure key exchange schemes are often misunderstood. It has been shown recently that the use of two pairs of resistors with enhanced Johnsonnoise and a Kirchhoff-loop -i.e., a Kirchhoff-Law-Johnson-Noise (KLJN) protocol -for secure key distribution leads to information theoretic security levels superior to those of today's quantum key distribution. This issue is becoming particularly timely because of the recent full cracks of practical quantum communicators, as shown in numerous peer-reviewed publications. The KLJN system is briefly surveyed here with discussions about the essential questions such as (i) perfect and imperfect security characteristics of the key distribution, and (ii) how these two types of securities can be unconditional (or information theoretical).

No abstract

Communicated by Zoltan GinglInstantaneous noise-based logic can avoid time-averaging, which implies significant potential for low-power parallel operations in beyond-Moore-law-chips. However, in its random-telegraph-wave representation, the complete uniform superposition (superposition of all N -bit binary numbers) will be zero with high probability, that is, non-zero with exponentially low probability, thus operations with the uniform superposition would require exponential time-complexity. To fix this deficiency, we modify the amplitudes of the signals of L and H states and achieve an exponential speedup compared to the old situation. Another improvement concerns the identification of a single product-string (hyperspace vector). We introduce "time shifted noise-based logic", which is constructed by shifting each reference signal with a small time delay. This modification implies an exponential speedup of single hyperspace vector identification compared to the former case and it requires the same, O(N ) complexity as in quantum computing.