Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block,and it plays a crucial role in environmental perception...Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block,and it plays a crucial role in environmental perception.Conventional learning-based visual semantic segmentation approaches count heavily on largescale training data with dense annotations and consistently fail to estimate accurate semantic labels for unseen categories.This obstruction spurs a craze for studying visual semantic segmentation with the assistance of few/zero-shot learning.The emergence and rapid progress of few/zero-shot visual semantic segmentation make it possible to learn unseen categories from a few labeled or even zero-labeled samples,which advances the extension to practical applications.Therefore,this paper focuses on the recently published few/zero-shot visual semantic segmentation methods varying from 2D to 3D space and explores the commonalities and discrepancies of technical settlements under different segmentation circumstances.Specifically,the preliminaries on few/zeroshot visual semantic segmentation,including the problem definitions,typical datasets,and technical remedies,are briefly reviewed and discussed.Moreover,three typical instantiations are involved to uncover the interactions of few/zero-shot learning with visual semantic segmentation,including image semantic segmentation,video object segmentation,and 3D segmentation.Finally,the future challenges of few/zero-shot visual semantic segmentation are discussed.展开更多
Metasurfaces,composed of planar arrays of intricately designed meta-atom structures,possess remarkable capabilities in controlling electromagnetic waves in various ways.A critical aspect of metasurface design involves...Metasurfaces,composed of planar arrays of intricately designed meta-atom structures,possess remarkable capabilities in controlling electromagnetic waves in various ways.A critical aspect of metasurface design involves selecting suitable meta-atoms to achieve target functionalities such as phase retardation,amplitude modulation,and polarization conversion.Conventional design processes often involve extensive parameter sweeping,a laborious and computationally intensive task heavily reliant on designer expertise and judgement.Here,we present an efficient genetic algorithm assisted meta-atom optimization method for high-performance metasurface optics,which is compatible to both single-and multiobjective device design tasks.We first employ the method for a single-objective design task and implement a high-efficiency Pancharatnam-Berry phase based metalens with an average focusing efficiency exceeding 80%in the visible spectrum.We then employ the method for a dual-objective metasurface design task and construct an efficient spin-multiplexed structural beam generator.The device is capable of generating zeroth-order and first-order Bessel beams respectively under right-handed and left-handed circular polarized illumination,with associated generation efficiencies surpassing 88%.Finally,we implement a wavelength and spin co-multiplexed four-channel metahologram capable of projecting two spin-multiplexed holographic images under each operational wavelength,with efficiencies over 50%.Our work offers a streamlined and easy-to-implement approach to meta-atom design and optimization,empowering designers to create diverse high-performance and multifunctional metasurface optics.展开更多
Information technology education has played a more important role under the background of“Internet+”.However,a combination of education and information technology is only limited between online teaching platforms an...Information technology education has played a more important role under the background of“Internet+”.However,a combination of education and information technology is only limited between online teaching platforms and massive open online courses(MOOC).This paper proposes a visual teaching system based on cloud computing and big data techniques via combing virtual and real techniques online and offline to provide rich teaching resources for students.It can also use the digital human-computer interaction answering function to address students’questions.Additionally,it can provide a medium for young teachers to quickly improve their professional teaching skills.This paper aims to achieve a multimedia system via integrating“Internet+”technology with education to help improve talent training and abilities of young teachers.展开更多
0 INTRODUCTION Chromium(Cr)is one of the most important strategic critical metals in China.The primary chromite deposits can be divided into two types according to their geological setting and occurrences:podiform chr...0 INTRODUCTION Chromium(Cr)is one of the most important strategic critical metals in China.The primary chromite deposits can be divided into two types according to their geological setting and occurrences:podiform chromite and stratiform/layered chromite(Stowe,1994;Paktunc,1990).Podiform chromites mainly occur in ophiolites or mantle peridotites(Yang et al.,2022,2010;Bao et al.,1999).展开更多
基金supported by National Key Research and Development Program of China(2021YFB1714300)the National Natural Science Foundation of China(62233005)+2 种基金in part by the CNPC Innovation Fund(2021D002-0902)Fundamental Research Funds for the Central Universities and Shanghai AI Labsponsored by Shanghai Gaofeng and Gaoyuan Project for University Academic Program Development。
文摘Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block,and it plays a crucial role in environmental perception.Conventional learning-based visual semantic segmentation approaches count heavily on largescale training data with dense annotations and consistently fail to estimate accurate semantic labels for unseen categories.This obstruction spurs a craze for studying visual semantic segmentation with the assistance of few/zero-shot learning.The emergence and rapid progress of few/zero-shot visual semantic segmentation make it possible to learn unseen categories from a few labeled or even zero-labeled samples,which advances the extension to practical applications.Therefore,this paper focuses on the recently published few/zero-shot visual semantic segmentation methods varying from 2D to 3D space and explores the commonalities and discrepancies of technical settlements under different segmentation circumstances.Specifically,the preliminaries on few/zeroshot visual semantic segmentation,including the problem definitions,typical datasets,and technical remedies,are briefly reviewed and discussed.Moreover,three typical instantiations are involved to uncover the interactions of few/zero-shot learning with visual semantic segmentation,including image semantic segmentation,video object segmentation,and 3D segmentation.Finally,the future challenges of few/zero-shot visual semantic segmentation are discussed.
基金support from the National Science Foundation of China(Grant Nos.62075078 and 62135004)the Knowledge Innovation Program of Wuhan-Shuguang Project(Grant No.2022010801020095).
文摘Metasurfaces,composed of planar arrays of intricately designed meta-atom structures,possess remarkable capabilities in controlling electromagnetic waves in various ways.A critical aspect of metasurface design involves selecting suitable meta-atoms to achieve target functionalities such as phase retardation,amplitude modulation,and polarization conversion.Conventional design processes often involve extensive parameter sweeping,a laborious and computationally intensive task heavily reliant on designer expertise and judgement.Here,we present an efficient genetic algorithm assisted meta-atom optimization method for high-performance metasurface optics,which is compatible to both single-and multiobjective device design tasks.We first employ the method for a single-objective design task and implement a high-efficiency Pancharatnam-Berry phase based metalens with an average focusing efficiency exceeding 80%in the visible spectrum.We then employ the method for a dual-objective metasurface design task and construct an efficient spin-multiplexed structural beam generator.The device is capable of generating zeroth-order and first-order Bessel beams respectively under right-handed and left-handed circular polarized illumination,with associated generation efficiencies surpassing 88%.Finally,we implement a wavelength and spin co-multiplexed four-channel metahologram capable of projecting two spin-multiplexed holographic images under each operational wavelength,with efficiencies over 50%.Our work offers a streamlined and easy-to-implement approach to meta-atom design and optimization,empowering designers to create diverse high-performance and multifunctional metasurface optics.
基金supported in part by the Ideological and Political Education of Financial Decision Support System under KVSZZZ202315in part by Collaborative Education by the Ministry of Education under 220501210164954in part by Teaching Education Reform of NPU under 06410-23GZ230106。
文摘Information technology education has played a more important role under the background of“Internet+”.However,a combination of education and information technology is only limited between online teaching platforms and massive open online courses(MOOC).This paper proposes a visual teaching system based on cloud computing and big data techniques via combing virtual and real techniques online and offline to provide rich teaching resources for students.It can also use the digital human-computer interaction answering function to address students’questions.Additionally,it can provide a medium for young teachers to quickly improve their professional teaching skills.This paper aims to achieve a multimedia system via integrating“Internet+”technology with education to help improve talent training and abilities of young teachers.
基金supported by projects from the Ministry of Science and Technology National Key R&D Pro-gram of China(No.2022YFC2903504)the National Natural Science Foundation of China(No.42321001)+1 种基金the Bureau of Geological Exploration&Development of Qinghai Province(No.2024-67)the Kunlun Talents Project of Qinghai Prov‐ince(2023).
文摘0 INTRODUCTION Chromium(Cr)is one of the most important strategic critical metals in China.The primary chromite deposits can be divided into two types according to their geological setting and occurrences:podiform chromite and stratiform/layered chromite(Stowe,1994;Paktunc,1990).Podiform chromites mainly occur in ophiolites or mantle peridotites(Yang et al.,2022,2010;Bao et al.,1999).
