Underwater images always suffer from low contrast and color distortion due to the wavelength-dependent scattering absorption effects caused by particles existing in turbid water, especially high turbidity conditions. Based on polarization properties of backscattering light, polarimetric methods can estimate intensity level transmittance media. Accordingly, they separate target signal undesired ones achieve high-quality imaging. In addition, learning-based are effective for gray-model image...

A flat 2.0 μm ultra broadband emission with a full width at half maximum (FWHM) of 329 nm is achieved in 1 mol.% Tm2O3 and 0.05 Ho2O3 co-doped gallium tellurite glasses upon the excitation an 808 laser diode. The influence Tm3+ Ho3+ contents on spectroscopic properties minutely investigated by absorption spectra, lifetime measurement. In addition, cross section gain coefficient ions are calculated, values reach 8.2 × 10−21 cm2 1.54 cm−1, respectively. Moreover, forward backward energy...

Currently, among the millions of Android applications, there exist numerous malicious programs that pose significant threats to people’s security and privacy. Therefore, it is imperative develop approaches for detecting malware. Recently developed malware detection methods usually rely on various features, such as application programming interface (API) sequences, images, permissions, thereby ignoring importance source code associated comments, which are not included in we propose...

Automatic malware detection was aimed at determining whether the application is malicious or not with automated systems. Android attacks have gained tremendous pace owing to widespread use of mobile devices. Although significant progress has been made in antimalware techniques, these methods mainly rely on program features, ignoring importance source code analysis. Furthermore, dynamic analysis low coverage and poor efficiency. Hence, we propose an automatic approach, named HyGNN-Mal. It...

Topology inference driven by non-collaborative or incomplete prior knowledge is widely used in pivotal target network sieving and completion. However, perceivable topology also allows attackers to identify the fragile bottlenecks perform efficacious attacks that are difficult defend against injecting indistinguishable low-volume attacks. Most existing countermeasures proposed obfuscate data set up honeypots with adversarial examples. there two challenges when adding perturbations live links...

In this Letter, we introduce a self-supervised depth estimation method based on polarization binocular imaging. First, an end-to-end disparity network is utilized to estimate the left and right disparities from stereo view images. Next, design loss functions that facilitate training of network, eliminating need for labeled data. The framework fully leverages strengths both effectiveness proposed algorithm validated using real underwater polarized

In this Letter, we introduce a self-supervised depth estimation method based on polarization binocular imaging. First, an end-to-end disparity network is utilized to estimate the left and right disparities from stereo view images. Next, design loss functions that facilitate training of network, eliminating need for labeled data. The framework fully leverages strengths both effectiveness proposed algorithm validated using real underwater polarized

In this Letter, we introduce a self-supervised depth estimation method based on polarization binocular imaging. First, an end-to-end disparity network is utilized to estimate the left and right disparities from stereo view images. Next, design loss functions that facilitate training of network, eliminating need for labeled data. The framework fully leverages strengths both effectiveness proposed algorithm validated using real underwater polarized

In this Letter, we introduce a self-supervised depth estimation method based on polarization binocular imaging. First, an end-to-end disparity network is utilized to estimate the left and right disparities from stereo view images. Next, design loss functions that facilitate training of network, eliminating need for labeled data. The framework fully leverages strengths both effectiveness proposed algorithm validated using real underwater polarized

In this Letter, we introduce a self-supervised depth estimation method based on polarization binocular imaging. First, an end-to-end disparity network is utilized to estimate the left and right disparities from stereo view images. Next, design loss functions that facilitate training of network, eliminating need for labeled data. The framework fully leverages strengths both effectiveness proposed algorithm validated using real underwater polarized

Pomegranate flowers as row materials were used for extraction of polysaccharides by water-extraction and alcohol-precipitation method. After purification, the physical chemical properties, structure, monosaccharide composition molecular weight studied. The results showed that from pomegranate mainly contained two kinds water soluble acidic polysaccharides, arabinose galactose, both hydroxyl, carboxyl, amino, hydroxyl radical, sulfate, beta glycosidic bond alpha structure. PP1 PP2 6.16 × 104...

The use of natural language processing to analyze binary data is a popular research topic in malware analysis. Embedding code into vector an important basis for building analysis neural network model. Current solutions focus on embedding instructions or basic block sequences vectors with recurrent models utilizing graph algorithm control flow graphs annotated generate representation vectors. In analysis, most these studies only the single structural information and rely one corpus. It...

With the rapid development of information technology, scale software has increased exponentially. Binary code similarity detection technology plays an important role in many fields, such as detecting plagiarism, vulnerabilities discovery, and copyright solution issues. Nevertheless, what cannot be ignored is that a variety approaches to binary semantic representation have been introduced recently, but few can catch up with existing obfuscation techniques due their maturing extensive...

Utilizing NLP methods in malware classification or clustering applications is a hotspot analysis. Binary embedding has become an important direction and basis for Existing binary vectorizing cannot extract semantic functional information simultaneously, which may affect the performance of family clustering. In this paper, novel feature fusion representation method proposed based on PV -DM (Paragraph Vector-Distributed Memory) model, K-Means algorithm adopted The combines features...