As the energy internet continues to advance, the degree of informatization of the power system has been continuously improved. However, finding out users' abnormal electricity consumption behavior is particularly ...
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Irregular boundaries in image stitching naturally occur due to freely moving *** deal with this problem,existing methods focus on optimizing mesh warping to make boundaries regular using the traditional explicit ***,p...
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Irregular boundaries in image stitching naturally occur due to freely moving *** deal with this problem,existing methods focus on optimizing mesh warping to make boundaries regular using the traditional explicit ***,previous methods always depend on hand-crafted features(e.g.,keypoints and line segments).Thus,failures often happen in overlapping regions without distinctive *** this paper,we address this problem by proposing RecStitchNet,a reasonable and effective network for image stitching with rectangular *** that both stitching and imposing rectangularity are non-trivial tasks in the learning-based framework,we propose a three-step progressive learning based strategy,which not only simplifies this task,but gradually achieves a good balance between stitching and imposing *** the first step,we perform initial stitching by a pre-trained state-of-the-art image stitching model,to produce initially warped stitching results without considering the boundary ***,we use a regression network with a comprehensive objective regarding mesh,perception,and shape to further encourage the stitched meshes to have rectangular boundaries with high content ***,we propose an unsupervised instance-wise optimization strategy to refine the stitched meshes iteratively,which can effectively improve the stitching results in terms of feature alignment,as well as boundary and structure *** to the lack of stitching datasets and the difficulty of label generation,we propose to generate a stitching dataset with rectangular stitched images as pseudo-ground-truth labels,and the performance upper bound induced from the it can be broken by our unsupervised *** and quantitative results and evaluations demonstrate the advantages of our method over the state-of-the-art.
Privacy and security issues concerning mobile devices have substantial consequences for individuals, groups, governments, and businesses. The Android operating system bolsters smartphone data protection by imposing re...
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We present a polymer optical fiber sensor doped with MAPbBr3 quantum dots for wearable temperature sensing. This sensor exhibits miniaturization, flexibility, and stretchability, with a temperature sensitivity of 1.74...
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With the successful manufacture of highly stable and high-performance satellite processors, caching on satellites has become possible. information Centric Networking (ICN) is introduced to satellite networks to addres...
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We demonstrate ultra-thin fiber accelerometers based on coherent phase detection. With ultra-thin membrane transducer design，the fiber accelerometers can realize multipoint and multi-directional vibration detection f...
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We presented an accurate and wearable microfiber-based sensor chip with an active pressure adaptation unit for cardiovascular assessment, exhibiting an accuracy of 93.75% for arteriosclerosis assessment and errors of ...
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The simultaneous detection of multiple stimuli,such as pressure and temperature,has long been a persistent challenge for developing electronic skin(eskin)to emulate the functionality of human ***,the demand for integr...
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The simultaneous detection of multiple stimuli,such as pressure and temperature,has long been a persistent challenge for developing electronic skin(eskin)to emulate the functionality of human ***,the demand for integrated power supply units is an additional pressing concern to achieve its lightweightness and ***,we propose a self-powered dual temperature–pressure(SPDM)sensor,which utilizes a compressible ionic gel electrolyte driven by the potential difference between MXene and Al *** SPDM sensor exhibits a rapid and timely response to changes in pressure-induced deformation,while exhibiting a slow and hysteretic response to temperature *** distinct response characteristics enable the differentiation of current signals generated by different stimuli through machine learning,resulting in an impressive accuracy rate of 99.1%.Furthermore,the developed SPDM sensor exhibits a wide pressure detection range of 0–800 kPa and a broad temperature detection range of 5–75C,encompassing the environmental conditions encountered in daily human *** dual-mode coupled strategy by machine learning provides an effective approach for temperature and pressure detection and discrimination,showcasing its potential applications in wearable electronics,intelligent robots,human–machine interactions,and so on.
We proposed an in-service OTDR based on native transmitters, which achieves rate matching without adding hardware complexity by introducing DSM. It achieves a dynamic range of >10 dB and a spatial resolution of 10 ...
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We present a polymer optical fiber sensor doped with MAPbBr3 quantum dots for wearable temperature sensing. This sensor exhibits miniaturization, flexibility, and stretchability, with a temperature sensitivity of 1.74...
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