254 research outputs found
Non-disturbance criteria of quantum measurements
Using the general sequential product proposed by Shen and Wu in [J. Phys. A:
Math. Theor. 42, 345203, 2009], we derive three criteria for describing
non-disturbance between quantum measurements that may be unsharp with such new
sequential products, which generalizes Gudder's results
Cardiovascular magnetic resonance of quinticuspid aortic valve with aortic regurgitation and dilated ascending aorta
We report a rare case of a quinticuspid aortic valve associated with regurgitation and dilation of the ascending aorta, which was diagnosed and post-surgically followed up by cardiovascular magnetic resonance and dual source computed tomography
Myocardial fibrosis in desmin-related hypertrophic cardiomyopathy
Desmin-related myopathy (DRM) is known to cause different types of cardiomyopathy. Late gadolinium enhancement cardiovascular magnetic resonance (CMR) has been shown to identify fibrosis in ischemic and non-ischemic cardiomyopathies. We present a rare case of desmin-related hypertrophic cardiomyopathy, CMR revealed fibrosis in the lateral wall of the left ventricle. CMR is superior to conventional echocardiography for the detection of myocardial fibrosis in desmin-related cardiomyopathy, which may be useful to detect early cardiac involvement and predict the patient prognosis
XVTP3D: Cross-view Trajectory Prediction Using Shared 3D Queries for Autonomous Driving
Trajectory prediction with uncertainty is a critical and challenging task for
autonomous driving. Nowadays, we can easily access sensor data represented in
multiple views. However, cross-view consistency has not been evaluated by the
existing models, which might lead to divergences between the multimodal
predictions from different views. It is not practical and effective when the
network does not comprehend the 3D scene, which could cause the downstream
module in a dilemma. Instead, we predicts multimodal trajectories while
maintaining cross-view consistency. We presented a cross-view trajectory
prediction method using shared 3D Queries (XVTP3D). We employ a set of 3D
queries shared across views to generate multi-goals that are cross-view
consistent. We also proposed a random mask method and coarse-to-fine
cross-attention to capture robust cross-view features. As far as we know, this
is the first work that introduces the outstanding top-down paradigm in BEV
detection field to a trajectory prediction problem. The results of experiments
on two publicly available datasets show that XVTP3D achieved state-of-the-art
performance with consistent cross-view predictions.Comment: 11 pages, 6 figures, accepted by IJCAI 2
Average skew information-based coherence and its typicality for random quantum states
We study the average skew information-based coherence for both random pure
and mixed states. The explicit formulae of the average skew information-based
coherence are derived and shown to be the functions of the dimension N of the
state space. We demonstrate that as N approaches to infinity, the average
coherence is 1 for random pure states, and a positive constant less than 1/2
for random mixed states. We also explore the typicality of average skew
information-based coherence of random quantum states. Furthermore, we identify
a coherent subspace such that the amount of the skew information-based
coherence for each pure state in this subspace can be bounded from below almost
always by a fixed number that is arbitrarily close to the typical value of
coherence.Comment: 24page
Coherence and complementarity based on modified generalized skew information
We introduce modified generalized Wigner-Yanase-Dyson (MGWYD) skew
information and modified weighted generalized Wigner-Yanase-Dyson (MWGWYD) skew
information. By revisiting state-channel interaction based on MGWYD skew
information, a family of coherence measures with respect to quantum channels is
proposed. Furthermore, explicit analytical expressions of these coherence
measures of qubit states are derived with respect to different quantum
channels. Moreover, complementarity relations based on MGWYD skew information
and MWGWYD skew information are also presented. Specifically, the conservation
relations are investigated, while two interpretations of them including
symmetry-asymmetry complementarity and wave-particle duality have been
proposed.Comment: 20page
All-in-one aerial image enhancement network for forest scenes
Drone monitoring plays an irreplaceable and significant role in forest firefighting due to its characteristics of wide-range observation and real-time messaging. However, aerial images are often susceptible to different degradation problems before performing high-level visual tasks including but not limited to smoke detection, fire classification, and regional localization. Recently, the majority of image enhancement methods are centered around particular types of degradation, necessitating the memory unit to accommodate different models for distinct scenarios in practical applications. Furthermore, such a paradigm requires wasted computational and storage resources to determine the type of degradation, making it difficult to meet the real-time and lightweight requirements of real-world scenarios. In this paper, we propose an All-in-one Image Enhancement Network (AIENet) that can restore various degraded images in one network. Specifically, we design a new multi-scale receptive field image enhancement block, which can better reconstruct high-resolution details of target regions of different sizes. In particular, this plug-and-play module enables it to be embedded in any learning-based model. And it has better flexibility and generalization in practical applications. This paper takes three challenging image enhancement tasks encountered in drone monitoring as examples, whereby we conduct task-specific and all-in-one image enhancement experiments on a synthetic forest dataset. The results show that the proposed AIENet outperforms the state-of-the-art image enhancement algorithms quantitatively and qualitatively. Furthermore, extra experiments on high-level vision detection also show the promising performance of our method compared with some recent baselines.Award-winningPostprint (published version
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