8,272 research outputs found
AON: Towards Arbitrarily-Oriented Text Recognition
Recognizing text from natural images is a hot research topic in computer
vision due to its various applications. Despite the enduring research of
several decades on optical character recognition (OCR), recognizing texts from
natural images is still a challenging task. This is because scene texts are
often in irregular (e.g. curved, arbitrarily-oriented or seriously distorted)
arrangements, which have not yet been well addressed in the literature.
Existing methods on text recognition mainly work with regular (horizontal and
frontal) texts and cannot be trivially generalized to handle irregular texts.
In this paper, we develop the arbitrary orientation network (AON) to directly
capture the deep features of irregular texts, which are combined into an
attention-based decoder to generate character sequence. The whole network can
be trained end-to-end by using only images and word-level annotations.
Extensive experiments on various benchmarks, including the CUTE80,
SVT-Perspective, IIIT5k, SVT and ICDAR datasets, show that the proposed
AON-based method achieves the-state-of-the-art performance in irregular
datasets, and is comparable to major existing methods in regular datasets.Comment: Accepted by CVPR201
Cross-modal Hashing with Semantic Deep Embedding
Cross-modal hashing has demonstrated advantages on fast retrieval tasks. It improves the quality of hash coding by exploiting semantic correlation across different modalities. In supervised cross-modal hashing, the learning of hash function replies on the quality of extracted features, for which deep learning models have been adopted to replace the traditional models based on handcraft features. All deep methods, however, have not sufficiently explored semantic correlation of modalities for the hashing process. In this paper, we introduce a novel end-to-end deep cross-modal hashing framework which integrates feature and hash-code learning into the same network. We take both between and within modalities data correlation into consideration, and propose a novel network structure and a loss function with dual semantic supervision for hash learning. This method ensures that the generated binary codes keep the semantic relationship of the original data points. Cross-modal retrieval experiments on commonly used benchmark datasets show that our method yields substantial performance improvement over several state-of-the-art hashing methods
Guardauto: A Decentralized Runtime Protection System for Autonomous Driving
Due to the broad attack surface and the lack of runtime protection, potential
safety and security threats hinder the real-life adoption of autonomous
vehicles. Although efforts have been made to mitigate some specific attacks,
there are few works on the protection of the self-driving system. This paper
presents a decentralized self-protection framework called Guardauto to protect
the self-driving system against runtime threats. First, Guardauto proposes an
isolation model to decouple the self-driving system and isolate its components
with a set of partitions. Second, Guardauto provides self-protection mechanisms
for each target component, which combines different methods to monitor the
target execution and plan adaption actions accordingly. Third, Guardauto
provides cooperation among local self-protection mechanisms to identify the
root-cause component in the case of cascading failures affecting multiple
components. A prototype has been implemented and evaluated on the open-source
autonomous driving system Autoware. Results show that Guardauto could
effectively mitigate runtime failures and attacks, and protect the control
system with acceptable performance overhead
On the external photon fields in Fermi bright blazars
The external Compton (EC) model is used to study the high energy emission of
some blazars, in which the external photon field is considered to dominate
inverse Compton radiation. We explore the properties of external photon field
through analyzing the FERMI LAT bright AGN sample within three months
detection. In the sample, assuming the high energy radiation of low synchrotron
peaked blazars from the EC process, we find that the external photon parameter
Uext/\nuext may not be a constant. Calculating synchrotron and inverse Compton
(IC) luminosity from the quasi-simultaneous broadband spectrum energy
distributions (SEDs), we find that they have an approximately linear relation.
This indicates that the ratio of external photon and magnetic energy density is
a constant in the comoving frame, implying that the Lorentz factor of the
emitting blob depends on external photon field and magnetic field. The result
gives a strong constraint on the jet dynamic model.Comment: 7 pages, 2 figure
Transmission performance of 90°-bend optical waveguides fabricated in fused silica by femtosecond laser inscription
The L-shape waveguide was written in fused silica using a femtosecond laser with beam shaping. The guiding structure supports good light turning; 0.88 dB/turn was achieved at the silica-air interface. By using the finite-different time-domain method, the turn loss due to the turning structure and refractive index of the L-shape waveguide has been simulated. The results show that the proposed method has unprecedented flexibility in fabricating a 90°-bend waveguide
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