Anchor-free object-detection methods achieve a significant advancement in field of computer vision,particularly in the realm of real-time inferences.However,in remote sensing object detection,anchor-free methods often...Anchor-free object-detection methods achieve a significant advancement in field of computer vision,particularly in the realm of real-time inferences.However,in remote sensing object detection,anchor-free methods often lack of capability in separating the foreground and background.This paper proposes an anchor-free method named probability-enhanced anchor-free detector(ProEnDet)for remote sensing object detection.First,a weighted bidirectional feature pyramid is used for feature extraction.Second,we introduce probability enhancement to strengthen the classification of the object’s foreground and background.The detector uses the logarithm likelihood as the final score to improve the classification of the foreground and background of the object.ProEnDet is verified using the DIOR and NWPU-VHR-10 datasets.The experiment achieved mean average precisions of 61.4 and 69.0 on the DIOR dataset and NWPU-VHR-10 dataset,respectively.ProEnDet achieves a speed of 32.4 FPS on the DIOR dataset,which satisfies the real-time requirements for remote-sensing object detection.展开更多
Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous human...Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous humaneffort to label the image. Within this field, other research endeavors utilize weakly supervised methods. Theseapproaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such asscribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised andedge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equippedwith a distinct decoder module dedicated to road extraction tasks. One of the branches is dedicated to generatingedge masks using edge detection algorithms and optimizing road edge details. The other two branches supervise themodel’s training by employing scribble labels and spreading scribble information throughout the image. To addressthe historical flaw that created pseudo-labels that are not updated with network training, we use mixup to blendprediction results dynamically and continually update new pseudo-labels to steer network training. Our solutiondemonstrates efficient operation by simultaneously considering both edge-mask aid and dynamic pseudo-labelsupport. The studies are conducted on three separate road datasets, which consist primarily of high-resolutionremote-sensing satellite photos and drone images. The experimental findings suggest that our methodologyperforms better than advanced scribble-supervised approaches and specific traditional fully supervised methods.展开更多
The Solar Upper Transition Region Imager(SUTRI)onboard the Space Advanced Technology demonstration satellite(SATech-01),which was launched to a Sun-synchronous orbit at a height of~500 km in 2022 July,aims to test the...The Solar Upper Transition Region Imager(SUTRI)onboard the Space Advanced Technology demonstration satellite(SATech-01),which was launched to a Sun-synchronous orbit at a height of~500 km in 2022 July,aims to test the on-orbit performance of our newly developed Sc/Si multi-layer reflecting mirror and the 2k×2k EUV CMOS imaging camera and to take full-disk solar images at the Ne VII 46.5 nm spectral line with a filter width of~3 nm.SUTRI employs a Ritchey-Chrétien optical system with an aperture of 18 cm.The on-orbit observations show that SUTRI images have a field of view of~416×416 and a moderate spatial resolution of~8″without an image stabilization system.The normal cadence of SUTRI images is 30 s and the solar observation time is about16 hr each day because the earth eclipse time accounts for about 1/3 of SATech-01's orbit period.Approximately15 GB data is acquired each day and made available online after processing.SUTRI images are valuable as the Ne VII 46.5 nm line is formed at a temperature regime of~0.5 MK in the solar atmosphere,which has rarely been sampled by existing solar imagers.SUTRI observations will establish connections between structures in the lower solar atmosphere and corona,and advance our understanding of various types of solar activity such as flares,filament eruptions,coronal jets and coronal mass ejections.展开更多
Considering the time-consuming and tedious work of the current methods to control plant layout,which is mostly based on expert experience or field trials,we propose an algorithm to optimize and simulate a planting lay...Considering the time-consuming and tedious work of the current methods to control plant layout,which is mostly based on expert experience or field trials,we propose an algorithm to optimize and simulate a planting layout based on a virtual plant model and an optimization algorithm.A functional-structural plant model,which combines the structure and physiological function of plants,is used to construct a planting scene.The planting and row spacing are set as the genetic factors and the chromosomes of the genetic algorithm are encoded with a binary method.The photosynthetic yield of the unit planting area is denoted as the fitness value.By using this method,the intercropping of maize and soybean plants and the sole cropping of rice plants are studied.Experimental results show that the proposed method can obtain a high yield planting plan.展开更多
There are two major research issues with regard to detoxification;one is pathological testing of drug users and the other is rehabilitation methods and techniques.Over the years,domestic and foreign researchers have d...There are two major research issues with regard to detoxification;one is pathological testing of drug users and the other is rehabilitation methods and techniques.Over the years,domestic and foreign researchers have done a lot of work on pathological changes in the brain and rehabilitation techniques for drug users.This article discusses the research status of these two aspects.At present,the evaluation of brain function in drug addicts is still dominated by a single electroencephalography(EEG),nearinfrared spectroscopy(NIRS),or magnetic resonance imaging scan.The multimodal physiological data acquisition method based on EEG–NIRS technique is relatively advantageous for actual physiological data acquisition.The traditional drug rehabilitation method is based on medication and psychological counseling.In recent years,psychological correction(e.g.,emotional ventilation,intelligent physical and mental decompression,virtual reality technique and drug addiction suppression system,sports training,and rehabilitation)and physical therapy(transcranial magnetic stimulation)have gradually spread.These rehabilitations focus on comprehensive treatment from the psychological and physical aspects.In recent years,new intervention ideas such as brain–computer interface technique have been continuously proposed.In this review,we have introduced multimodal brain function detection and rehabilitation intervention,which have theoretical and practical significance in drug rehabilitation research.展开更多
基金supported in part by the National Natural Science Foundation of China(42001408).
文摘Anchor-free object-detection methods achieve a significant advancement in field of computer vision,particularly in the realm of real-time inferences.However,in remote sensing object detection,anchor-free methods often lack of capability in separating the foreground and background.This paper proposes an anchor-free method named probability-enhanced anchor-free detector(ProEnDet)for remote sensing object detection.First,a weighted bidirectional feature pyramid is used for feature extraction.Second,we introduce probability enhancement to strengthen the classification of the object’s foreground and background.The detector uses the logarithm likelihood as the final score to improve the classification of the foreground and background of the object.ProEnDet is verified using the DIOR and NWPU-VHR-10 datasets.The experiment achieved mean average precisions of 61.4 and 69.0 on the DIOR dataset and NWPU-VHR-10 dataset,respectively.ProEnDet achieves a speed of 32.4 FPS on the DIOR dataset,which satisfies the real-time requirements for remote-sensing object detection.
基金the National Natural Science Foundation of China(42001408,61806097).
文摘Significant advancements have been achieved in road surface extraction based on high-resolution remote sensingimage processing. Most current methods rely on fully supervised learning, which necessitates enormous humaneffort to label the image. Within this field, other research endeavors utilize weakly supervised methods. Theseapproaches aim to reduce the expenses associated with annotation by leveraging sparsely annotated data, such asscribbles. This paper presents a novel technique called a weakly supervised network using scribble-supervised andedge-mask (WSSE-net). This network is a three-branch network architecture, whereby each branch is equippedwith a distinct decoder module dedicated to road extraction tasks. One of the branches is dedicated to generatingedge masks using edge detection algorithms and optimizing road edge details. The other two branches supervise themodel’s training by employing scribble labels and spreading scribble information throughout the image. To addressthe historical flaw that created pseudo-labels that are not updated with network training, we use mixup to blendprediction results dynamically and continually update new pseudo-labels to steer network training. Our solutiondemonstrates efficient operation by simultaneously considering both edge-mask aid and dynamic pseudo-labelsupport. The studies are conducted on three separate road datasets, which consist primarily of high-resolutionremote-sensing satellite photos and drone images. The experimental findings suggest that our methodologyperforms better than advanced scribble-supervised approaches and specific traditional fully supervised methods.
基金supported by the National Natural Science Foundation of China(NSFC)under Grants 11825301,12003016,12073077the National Key R&D Program of China No.2021YFA0718600+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences with the Grant No.XDA15018400the Youth Innovation Promotion Association of CAS(2023061)。
文摘The Solar Upper Transition Region Imager(SUTRI)onboard the Space Advanced Technology demonstration satellite(SATech-01),which was launched to a Sun-synchronous orbit at a height of~500 km in 2022 July,aims to test the on-orbit performance of our newly developed Sc/Si multi-layer reflecting mirror and the 2k×2k EUV CMOS imaging camera and to take full-disk solar images at the Ne VII 46.5 nm spectral line with a filter width of~3 nm.SUTRI employs a Ritchey-Chrétien optical system with an aperture of 18 cm.The on-orbit observations show that SUTRI images have a field of view of~416×416 and a moderate spatial resolution of~8″without an image stabilization system.The normal cadence of SUTRI images is 30 s and the solar observation time is about16 hr each day because the earth eclipse time accounts for about 1/3 of SATech-01's orbit period.Approximately15 GB data is acquired each day and made available online after processing.SUTRI images are valuable as the Ne VII 46.5 nm line is formed at a temperature regime of~0.5 MK in the solar atmosphere,which has rarely been sampled by existing solar imagers.SUTRI observations will establish connections between structures in the lower solar atmosphere and corona,and advance our understanding of various types of solar activity such as flares,filament eruptions,coronal jets and coronal mass ejections.
基金This work was supported by the Natural Science Foundations of Zhejiang Province(LY18C130012)and the National Natural Science Foundations of China(31471416)The authors are grateful to the anonymous reviewers whose comments helped to improve this paper.
文摘Considering the time-consuming and tedious work of the current methods to control plant layout,which is mostly based on expert experience or field trials,we propose an algorithm to optimize and simulate a planting layout based on a virtual plant model and an optimization algorithm.A functional-structural plant model,which combines the structure and physiological function of plants,is used to construct a planting scene.The planting and row spacing are set as the genetic factors and the chromosomes of the genetic algorithm are encoded with a binary method.The photosynthetic yield of the unit planting area is denoted as the fitness value.By using this method,the intercropping of maize and soybean plants and the sole cropping of rice plants are studied.Experimental results show that the proposed method can obtain a high yield planting plan.
基金supported by Key Research&Development Project of National Science and Technique Ministry of China(No.2018YFC-0807405,No.2018YFC1312903)National Defense Basic Scientific Research Program of China(No.JCKY2017413C002)+2 种基金National Natural Science Foundation of China(No.61976133)111 Project(No.D18003)Scientific Research Project of Theoretical Research on Drug Rehabilitation of Judicial Administration of the People’s Republic of China(No.19ZD03)
文摘There are two major research issues with regard to detoxification;one is pathological testing of drug users and the other is rehabilitation methods and techniques.Over the years,domestic and foreign researchers have done a lot of work on pathological changes in the brain and rehabilitation techniques for drug users.This article discusses the research status of these two aspects.At present,the evaluation of brain function in drug addicts is still dominated by a single electroencephalography(EEG),nearinfrared spectroscopy(NIRS),or magnetic resonance imaging scan.The multimodal physiological data acquisition method based on EEG–NIRS technique is relatively advantageous for actual physiological data acquisition.The traditional drug rehabilitation method is based on medication and psychological counseling.In recent years,psychological correction(e.g.,emotional ventilation,intelligent physical and mental decompression,virtual reality technique and drug addiction suppression system,sports training,and rehabilitation)and physical therapy(transcranial magnetic stimulation)have gradually spread.These rehabilitations focus on comprehensive treatment from the psychological and physical aspects.In recent years,new intervention ideas such as brain–computer interface technique have been continuously proposed.In this review,we have introduced multimodal brain function detection and rehabilitation intervention,which have theoretical and practical significance in drug rehabilitation research.
