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Underwater obstacle detection is essential for safe deployment of autonomous underwater vehicles (AUVs). In this paper, we make an attempt to explore one kind of underwater obstacle detection strategy with the help of the Relative Total Variation(RTV) and Joint Guided Filtering(JGF). We first introduce one kind of virtual retinex model. Then we utilize the Relative Total Variation to extract the essential...
This paper studies a formation control problem for multiple mobile robot systems with model uncertainty. The formation is achieved by a distributed robust predictive control algorithm. Firstly, a distributed model of the formation system is derived by using the path tracking error dynamic of single mobile robot. Considering the error of linearization and measurement error caused by the accelerometer...
Object part segmentation is a challenging and fundamental problem in computer vision. Its difficulties may be caused by the varying viewpoints, poses, and topological structures, which can be attributed to an essential reason, i.e., a specific object is a 3D model rather than a 2D figure. Therefore, we conjecture that not only 2D appearance features but also 3D geometric features could be helpful...
In this paper, we would like to review and present our latest progress on microwave photonic signal transmission and processing, including linearization of analog photonic link, generation of ultrapure radiofrequency signal and elimination of self-interference.
The ability of learning from noisy labels is very useful in many visual recognition tasks, as a vast amount of data with noisy labels are relatively easy to obtain. Traditionally, label noise has been treated as statistical outliers, and techniques such as importance re-weighting and bootstrapping have been proposed to alleviate the problem. According to our observation, the real-world noisy labels...
Recently, CNN-based models have achieved remarkable success in image-based salient object detection (SOD). In these models, a key issue is to find a proper network architecture that best fits for the task of SOD. Toward this end, this paper proposes two-stream fixation-semantic CNNs, whose architecture is inspired by the fact that salient objects in complex images can be unambiguously annotated by...
This paper proposes a novel approach for segmenting primary video objects by using Complementary Convolutional Neural Networks (CCNN) and neighborhood reversible flow. The proposed approach first pre-trains CCNN on massive images with manually annotated salient objects in an end-to-end manner, and the trained CCNN has two separate branches that simultaneously handle two complementary tasks, i.e.,...
Pathologic microvasculature plays a key role in the leading causes of blindness including diabetic retinopathy, retinal vein occlusions, and macular degeneration. Current treatments, including laser therapy, photodynamic therapy (PDT), and anti-vascular endothelial growth factor (VEGF) therapy, impose significant burdens on patients, their families, and our health system because of frequent administration,...
The AIS broadcasts the ship's navigation data automatically and autonomously through VHF band. It plays an important role in collision avoidance and maritime situational awareness. However, in inland waterways, it is common that the AIS data-link was obstructed by the river bank and mountains, or sometimes the AIS was encountered with the electromagnetic interference. Consequently, the AIS dynamic...
The ECD have been considered critical process for PCB industry, yet the catalysts with high performance are of great importance in this process. In this work, PdCu bimetallic alloyed catalyst for Electroless copper deposition (ECD) were proposed by reducing the mixed metallic precursor with a simple hydrothermal method. The tunable Pd/Cu ratio plays key role of the morphologies and the electro-catalytic...
AIS data are of great significance to ensure the safety of ship navigation and strengthen maritime management. The present study focuses on the situations of AIS data loss in practical applications to research coverage of AIS base station. The original AIS data is pre-processed in accordance with structure characteristics, including data packet, data filtering and so on. Data reconstruction has been...
In this paper, we reported the performances of epoxy conductive adhesives filled with a low-melting-point Sn-Bi-Ag alloy. Results revealed the excellent stability, mechanical property of the Sn-Bi-Ag epoxy adhesives. Meanwhile, the thermal conductivity increased by increasing the content of Sn-Bi-Ag filler and 18 W m−1 K−1 can be obtained with 85% Sn-Bi-Ag filler content.
In this paper, we propose and experimentally demonstrate a linearization technique to modify the nonlinear transfer function of a phase modulation link. The phase modulation signal is converted into intensity modulation signal, and the phase of the optical carrier band is shifted. Eventually the third-order intermodulation distortion (IMD3) components produced by different optical spectrum components...
Dense captioning is a newly emerging computer vision topic for understanding images with dense language descriptions. The goal is to densely detect visual concepts (e.g., objects, object parts, and interactions between them) from images, labeling each with a short descriptive phrase. We identify two key challenges of dense captioning that need to be properly addressed when tackling the problem. First,...
Finding what is and what is not a salient object can be helpful in developing better features and models in salient object detection (SOD). In this paper, we investigate the images that are selected and discarded in constructing a new SOD dataset and find that many similar candidates, complex shape and low objectness are three main attributes of many non-salient objects. Moreover, objects may have...
Image captioning is a challenging problem owing to the complexity in understanding the image content and diverse ways of describing it in natural language. Recent advances in deep neural networks have substantially improved the performance of this task. Most state-of-the-art approaches follow an encoder-decoder framework, which generates captions using a sequential recurrent prediction model. However,...
Detecting faces with occlusions is a challenging task due to two main reasons: 1) the absence of large datasets of masked faces, and 2) the absence of facial cues from the masked regions. To address these two issues, this paper first introduces a dataset, denoted as MAFA, with 30, 811 Internet images and 35, 806 masked faces. Faces in the dataset have various orientations and occlusion degrees, while...
Phase images derived from imaging devices are usually wrapped into discontinuous images, so phase unwrapping is needed for phase image reconstruction. The wrap counts of every voxel are determined by the assumption that the true phase is spatially continuous. However, it is difficult to distinguish whether the phase jump is caused by phase wrap or noise. In this paper, a new 3D phase unwrapping method...
This paper studies ordering problem and logistics distribution of the distribution center in the supply chain. From the perspective of supply chain integration, considering inventory capacity constraints of distribution center and vehicle routing constraints, the optimization model of ordering and distribution are proposed firstly and the average total costs are minimized. In the process of logistics...
A dual-mode bandpass filter with compact size is proposed by using a new type of rotational symmetric dual-mode rectangular resonator. Due to the feed structure, two transmission zeros are generated near the lower and upper passbands to improve the skirt-selectivity of the filter. By adjusting the mutual coupling between the loading meander-line loop resonators, one transmission pole and neighboring...
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