1 A possible ancient shoreline has been found in the region of Mars explored by the Chinese rover,Zhurong,providing further evidence that an ocean may once have covered a vast area of the lowlands in the planet's ...1 A possible ancient shoreline has been found in the region of Mars explored by the Chinese rover,Zhurong,providing further evidence that an ocean may once have covered a vast area of the lowlands in the planet's northern part.2 The rover landed in southern Utopia Planitia in May 2021 and remained active for almost a year.Researchers studying data from the rover have found clues of an ancient ocean or liquid water as recently as 400,000 years ago.展开更多
Astronomers(天文学家)have discovered 128 new moons orbiting the planet Saturn.Now Saturn has 274 moons in total.Saturn holds the title“king of the moons”because it’s the planet with the most moons in our solar syst...Astronomers(天文学家)have discovered 128 new moons orbiting the planet Saturn.Now Saturn has 274 moons in total.Saturn holds the title“king of the moons”because it’s the planet with the most moons in our solar system(太阳系).Jupiter(木星)comes in second with 95 known moons.展开更多
Planetary surfaces,shaped by billions of years of geologic evolution,display numerous impact craters whose distribution of size,density,and spatial arrangement reveals the celestial body's history.Identifying thes...Planetary surfaces,shaped by billions of years of geologic evolution,display numerous impact craters whose distribution of size,density,and spatial arrangement reveals the celestial body's history.Identifying these craters is essential for planetary science and is currently mainly achieved with deep learning-driven detection algorithms.However,because impact crater characteristics are substantially affected by the geologic environment,surface materials,and atmospheric conditions,the performance of deep learning models can be inconsistent between celestial bodies.In this paper,we first examine how the surface characteristics of the Moon,Mars,and Earth,along with the differences in their impact crater features,affect model performance.Then,we compare crater detection across celestial bodies by analyzing enhanced convolutional neural networks and U-shaped Convolutional Neural Network-based models to highlight how geology,data,and model design affect accuracy and generalization.Finally,we address current deep learning challenges,suggest directions for model improvement,such as multimodal data fusion and cross-planet learning and list available impact crater databases.This review can provide necessary technical support for deep space exploration and planetary science,as well as new ideas and directions for future research on automatic detection of impact craters on celestial body surfaces and on planetary geology.展开更多
文摘1 A possible ancient shoreline has been found in the region of Mars explored by the Chinese rover,Zhurong,providing further evidence that an ocean may once have covered a vast area of the lowlands in the planet's northern part.2 The rover landed in southern Utopia Planitia in May 2021 and remained active for almost a year.Researchers studying data from the rover have found clues of an ancient ocean or liquid water as recently as 400,000 years ago.
文摘Astronomers(天文学家)have discovered 128 new moons orbiting the planet Saturn.Now Saturn has 274 moons in total.Saturn holds the title“king of the moons”because it’s the planet with the most moons in our solar system(太阳系).Jupiter(木星)comes in second with 95 known moons.
基金funded by the National Natural Science Foundation of China(12363009 and 12103020)Natural Science Foundation of Jiangxi Province(20224BAB211011)+1 种基金Youth Talent Project of Science and Technology Plan of Ganzhou(2022CXRC9191 and 2023CYZ26970)Jiangxi Province Graduate Innovation Special Funds Project(YC2024-S529 and YC2023-S672).
文摘Planetary surfaces,shaped by billions of years of geologic evolution,display numerous impact craters whose distribution of size,density,and spatial arrangement reveals the celestial body's history.Identifying these craters is essential for planetary science and is currently mainly achieved with deep learning-driven detection algorithms.However,because impact crater characteristics are substantially affected by the geologic environment,surface materials,and atmospheric conditions,the performance of deep learning models can be inconsistent between celestial bodies.In this paper,we first examine how the surface characteristics of the Moon,Mars,and Earth,along with the differences in their impact crater features,affect model performance.Then,we compare crater detection across celestial bodies by analyzing enhanced convolutional neural networks and U-shaped Convolutional Neural Network-based models to highlight how geology,data,and model design affect accuracy and generalization.Finally,we address current deep learning challenges,suggest directions for model improvement,such as multimodal data fusion and cross-planet learning and list available impact crater databases.This review can provide necessary technical support for deep space exploration and planetary science,as well as new ideas and directions for future research on automatic detection of impact craters on celestial body surfaces and on planetary geology.
