It is demonstrated that SAFARI under unreliable communications is guaranteed to converge at the same rate as the standard FedAvg with perfect communications.
Differently, our network is designed to refine the initial normal of each point by extracting additional information from multiple feature representations.
Experimental results verifythe feasibility of using alpha stable model to describe the IQSD, and prove the effectiveness of objective alpha stable model basedIQSD prediction method.
In this paper, we develop a new optimal LAS method in the TDBS, namely LAS-SDT, by taking advantage of the sequential Doppler shift and TOA measurements.
Video content is multifaceted, consisting of objects, scenes, interactions or actions.
Numerical results in a 3D scenario verify the theoretical analysis that the estimation accuracy of the new CFTWLAS method reaches CRLB in the presented experiments when the number of the ANs is large, the geometry is appropriate, and the noise is small.
The network traffic classification (NTC) is an essential tool to explore behaviours of network flows, and NTC is required for Internet service providers (ISPs) to manage the performance of the IoT network.
To the best of the authors' knowledge, this is the first measurement study and analysis conducted using a commercial cloud VR gaming platform, and under both fixed and adaptive bitrate streaming.
This work demonstrates that it is practicable for the blind people to feel the world through the brush in their hands.
Second, we further establish communication channels between low-frequency maps and high-frequency maps to interactively capture structures from high-frequency maps and add them back to low-frequency maps and, simultaneously, extract details from low-frequency maps and send them back to high-frequency maps, thereby removing rain streaks while preserving more delicate features in the input image.
Our method tends to synthesize plausible layouts and objects, respecting the interplay of multiple objects in an image.
In this article, we design a new time-of-arrival (TOA) system for simultaneous user device (UD) localization and synchronization with a periodic asymmetric ranging network, namely PARN.
Second, aggregating channels could help our model to concentrate on channels more related to image background instead of rain streaks.
In two-way time-of-arrival (TOA) systems, a user device (UD) obtains its position by round-trip communications to a number of anchor nodes (ANs) at known locations.
In this paper, we propose a post-hoc method, named Attribute-guided Metric Distillation (AMD), to explain existing ReID models.
Ranked #36 on Person Re-Identification on DukeMTMC-reID
Compared with the conventional iterative method, the proposed new CFJLAS method does not require initialization, obtains the optimal solution under the small noise condition, and has a low computational complexity.
We show that the LSPM-D is a special case of the LSPM-KVD when the UD is stationary with zero velocity.
Numerical results verify the theoretical analysis on positioning accuracy, and show that the new CDL method has superior performance over the state-of-the-art closed-form method.
We show that the conventional two-way TOA method is a special case of the TWLAS when the UD is stationary, and the TWLAS has high estimation accuracy than the conventional one-way TOA method.
This paper presents an unobtrusive solution that can automatically identify deep breath when a person is walking past the global depth camera.
Sturge-Weber syndrome (SWS) is a vascular malformation disease, and it may cause blindness if the patient's condition is severe.
To start with, we present an overview of the end-to-end deep face recognition.
To solve this problem, this paper presents a new homogeneous transformation model termed deep homogeneous feature fusion (DHFF) based on image style transfer (IST).
During the epidemic prevention and control period, our study can be helpful in prognosis, diagnosis and screening for the patients infected with COVID-19 (the novel coronavirus) based on breathing characteristics.
Binary image segmentation plays an important role in computer vision and has been widely used in many applications such as image and video editing, object extraction, and photo composition.
Based on this error map, both the sparse codes of rain and non-rain dictionaries are used jointly to represent the image structures of objects and avoid the edge artifacts in the non-rain regions.
Next, residual rain patches are selected randomly, and then added to the given target image along a raster scanning direction.
This paper introduces a new coloring method to add colors to near-infrared gray images based on a contrast-preserving mapping model.
It is also shown that the proposed color regularization can remove the edge artifacts which arise from the use of the conventional dark prior model.
We propose a weighted variational model to estimate both the reflectance and the illumination from an observed image.
Ranked #3 on Low-Light Image Enhancement on MEF
The size of the dictionary and the patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables.