Unsupervised Domain Adaptation for Disguised-gait-based Person Identification on Micro-Doppler Signatures

In recent years, gait-based person identification has gained significant interest for a variety of applications, including security systems and public security forensics. Meanwhile, this task is faced with the challenge of disguised gaits. When a human subject changes what he or she is wearing or carrying, it becomes challenging to reliably...

Prior-Guided Deep Interference Mitigation for FMCW Radars

In this article, the interference mitigation (IM) problem is tackled as a regression problem. A prior-guided deep learning (DL)-based IM approach is proposed for frequency-modulated continuous-wave (FMCW) radars. Considering the complex-valued nature of radar signals, a complex-valued convolutional neural network, which is different from the...

Geographical spatial analysis and risk prediction based on machine learning for maritime traffic accidents: A case study of Fujian sea area

Safety analysis according to the spatial distribution characteristics of maritime traffic accidents is critical to maritime traffic safety management. An accident analysis framework based on the geographic information system (GIS) is proposed to characterize the spatial distribution of maritime traffic accidents occurring in the Fujian sea area...

Joint Feature Synthesis and Embedding: Adversarial Cross-Modal Retrieval Revisited

Recently, generative adversarial network (GAN) has shown its strong ability on modeling data distribution via adversarial learning. Cross-modal GAN, which attempts to utilize the power of GAN to model the cross-modal joint distribution and to learn compatible cross-modal features, is becoming the research hotspot. However, the existing cross...

The effect of sulfate-rich sewage sludge ash on the volume deformation and micorstructure of cement paste

Sewage sludge ash (SSA) is the combustion residue of the sewage sludge obtained from wastewater treatment plants. In China, SSA normally contains high content of SO3, which may cause detrimental effect on the volume stability of cement-based materials. This study investigated the effect of sulfate-rich SSA (SR-SSA) on the volume deformation and...

Analysis of Railway Ballasted Track Stiffness and Behavior with a Hybrid Discrete-Continuum Approach

Railway ballasted track stiffness is an important indicator to identify supporting condition that ensures that the facility is well designed and functioned. Although many studies have been performed on track stiffness based on experimental tests and finite-element methods, the factors influencing the track stiffness have not been completely...

A One-Class Classification Method for Human Gait Authentication Using Micro-Doppler Signatures

In this letter, a radar-based gait authentication method is proposed. We focus on the overfitting problem on the target category caused by limited training data in authentication models and propose a one-class classification model to alleviate this problem. The effectiveness of such model is verified by establishing a radar-based gait dataset,...

Macro-meso dynamic analysis of railway transition zone: Hybrid DEM/FDM simulation and experimental validation

To probe into the mechanical behaviour of railway transition zone from the macro-meso aspects, a numerical model of transition zone is built that hybrids the Discrete Element Method (DEM) and Finite Difference Method (FDM). The DEM is utilised to simulate the ballast bed and sleeper, because it can consider the realistic ballast shapes and...

Matching images and text with multi-modal tensor fusion and re-ranking

A major challenge in matching images and text is that they have intrinsically different data distributions and feature representations. Most existing approaches are based either on embedding or classification, the first one mapping image and text instances into a common embedding space for distance measuring, and the second one regarding...

Denoising controlled-source electromagnetic data using least-squares inversion

Strong noise is one of the toughest problems in the controlled-source electromagnetic (CSEM) method, which highly affects the quality of recorded data. The three main types of noise existing in CSEM data are periodic noise, Gaussian white noise, and nonperiodic noise, among which the nonperiodic noise is thought to be the most difficult to...

Video Captioning by Adversarial LSTM

In this paper, we propose a novel approach to video captioning based on adversarial learning and long short-term memory (LSTM). With this solution concept, we aim at compensating for the deficiencies of LSTM-based video captioning methods that generally show potential to effectively handle temporal nature of video data when generating...

Adversarial Cross-Modal Retrieval

Cross-modal retrieval aims to enable flexible retrieval experience across different modalities (e.g., texts vs. images). The core of crossmodal retrieval research is to learn a common subspace where the items of different modalities can be directly compared to each other. In this paper, we present a novel Adversarial Cross-Modal Retrieval ...