作者: observatory 時(shí)間: 2025-3-21 22:17
https://doi.org/10.1007/978-3-031-25056-9artificial intelligence; computer networks; computer vision; data security; face recognition; gesture rec作者: 婚姻生活 時(shí)間: 2025-3-22 00:58 作者: Ruptured-Disk 時(shí)間: 2025-3-22 06:13
Computer Vision – ECCV 2022 Workshops978-3-031-25056-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 變化 時(shí)間: 2025-3-22 09:38
The Effects of Noise on Aquatic Lifeontact (TTC) with the surface during ventral landing. This is achieved by estimating divergence (inverse TTC), which is the rate of radial optic flow, from the event stream generated during landing. Our core contributions are a novel contrast maximisation formulation for event-based divergence estim作者: perpetual 時(shí)間: 2025-3-22 13:17
Arthur N. Popper,Anthony D. Hawkinsr space-based EO systems. Since the development of on-orbit AI applications requires rarely available raw data, training of these AI networks remains a challenge. To address this issue, we investigate the effects of varying two key image parameters between training and testing data on a ship segment作者: perpetual 時(shí)間: 2025-3-22 18:13
Alexander S. Douglass,Shima Abadilgorithms for pose estimation employ data-driven techniques. However, there is an absence of real training data for spacecraft imaged in space conditions due to the costs and difficulties associated with the space environment. This has motivated the introduction of 3D data simulators, solving the is作者: Ablation 時(shí)間: 2025-3-22 21:34
Arthur N. Popper,Anthony Hawkins cameras. The idea is to generate a 3D scene of Mars’ surface to address key challenges in planetary surface exploration such as: planetary geology, simulated navigation and shape analysis. Although there exist different methods to enable a 3D reconstruction of Mars’ surface, they rely on classical 作者: 冰河期 時(shí)間: 2025-3-23 03:41
Hearing, Noise, and Echolocating Odontocetesbased telescopes. Event cameras provide high-dynamic range, high temporal resolution, low latency asynchronous “event” data that captures illumination changes in a scene. Such data is ideally suited for estimating star motion since it has minimal image blur and can capture low-intensity changes in i作者: 史前 時(shí)間: 2025-3-23 07:35
Arthur N. Popper,Anthony Hawkinsal resolution of multiple images containing the same target. Increasing the resolution of images through super-resolution (SR) techniques can improve the performance of commodity optical hardware, allowing more science to be done with cheaper equipment. Many SR techniques rely on the accurate regist作者: 惰性氣體 時(shí)間: 2025-3-23 11:35
Mathias H. Andersson,Torbj?rn Johanssonrtian terrain segmentation has been critical for rover navigation and hazard avoidance to perform further exploratory tasks, e.g. soil sample collection and searching for organic compounds. Current Martian terrain segmentation models require a large amount of labeled data to achieve acceptable perfo作者: Stress-Fracture 時(shí)間: 2025-3-23 14:30 作者: Genome 時(shí)間: 2025-3-23 22:05 作者: evaculate 時(shí)間: 2025-3-23 23:01
Familial Factors and Substance Use Disordersportant scientific questions: the Hubble constant (.) tension. The commonly used Markov chain Monte Carlo (MCMC) method has been too time-consuming to achieve this goal, yet recent work has shown that convolution neural networks (CNNs) can be an alternative with seven orders of magnitude improvement作者: Detoxification 時(shí)間: 2025-3-24 04:49 作者: finite 時(shí)間: 2025-3-24 06:58
https://doi.org/10.1007/978-981-99-6335-5astive learning can be applied to hundreds of thousands of unlabeled Mars terrain images, collected from the Mars rovers Curiosity and Perseverance, and from the Mars Reconnaissance Orbiter. Such methods are appealing since the vast majority of Mars images are unlabeled as manual annotation is labor作者: 打火石 時(shí)間: 2025-3-24 11:39 作者: 使苦惱 時(shí)間: 2025-3-24 16:25 作者: 比喻好 時(shí)間: 2025-3-24 21:09 作者: Petechiae 時(shí)間: 2025-3-25 01:02
https://doi.org/10.1007/978-981-99-6335-5onal and spatially organized inputs such as images. However, their Transfer Learning (TL) properties are not yet well studied, and it is not fully known whether these neural architectures can transfer across different domains as well as CNNs. In this paper we study whether VTs that are pre-trained o作者: 含水層 時(shí)間: 2025-3-25 04:07
https://doi.org/10.1007/978-981-99-6335-5nder different light conditions. This can be later used to reveal surface details and interactively relight the subject. Such process, however, typically requires dedicated hardware setups to recover the light direction from multiple locations, making the process tedious when performed outside the l作者: FLIC 時(shí)間: 2025-3-25 07:40 作者: 性別 時(shí)間: 2025-3-25 15:28
The Effects of Noise on Aquatic Life our method. Owing to global optimisation, our algorithm is much more capable at recovering the true divergence, compared to other heuristic divergence estimators or event-based optic flow methods. With GPU acceleration, our method also achieves competitive runtimes.作者: Paleontology 時(shí)間: 2025-3-25 18:36
Arthur N. Popper,Anthony D. Hawkinsdata augmentation. By preparing models at the training stage for the appropriate feature space, the need for additional computational resources on-board for e.g. image scaling or band-alignment of camera data can be mitigated.作者: 聯(lián)合 時(shí)間: 2025-3-25 21:11 作者: 笨拙處理 時(shí)間: 2025-3-26 00:16 作者: avulsion 時(shí)間: 2025-3-26 04:33 作者: 難取悅 時(shí)間: 2025-3-26 10:48 作者: 狂亂 時(shí)間: 2025-3-26 15:57
Spacecraft Pose Estimation Based on?Unsupervised Domain Adaptation and?on a?3D-Guided Loss Combinatiomain adaptation with robust pseudo-labelling. Our solution has ranked second in the two categories of the 2021 Pose Estimation Challenge organised by the European Space Agency and the Stanford University, achieving the lowest average error over the two categories (Code is available at: .).作者: Immunization 時(shí)間: 2025-3-26 18:20
Monocular 6-DoF Pose Estimation for?Non-cooperative Spacecrafts Using Riemannian Regression Networkon and limits the error to a desirable range. Moreover, several data augmentation techniques were proposed to address the overfitting issue caused by the small scale of the spacecraft dataset in this paper. In the SPARK2022 challenge, our method achieves state-of-the-art pose estimation accuracy.作者: 大猩猩 時(shí)間: 2025-3-27 00:32 作者: 偏離 時(shí)間: 2025-3-27 05:11
Hearing, Noise, and Echolocating Odontoceteschronously to update a Kalman filter that estimates star position and velocity in an image. The proposed tracking method is validated on real and simulated data and shows state-of-that-art tracking performance against existing approach.作者: 總 時(shí)間: 2025-3-27 05:35 作者: Ingest 時(shí)間: 2025-3-27 12:55
https://doi.org/10.1007/978-981-99-6335-5, tailoring the style parameterization on a per-region basis using a semantic map of the facial regions. We show HyperNST to exceed state of the art in content preservation for our stylized content while retaining good style transfer performance.作者: 不如屎殼郎 時(shí)間: 2025-3-27 15:22
https://doi.org/10.1007/978-981-99-6335-5t classification problems and use them as a surrogate for studying the TL potential of four popular VTs. Their performance is extensively compared against that of four common CNNs across several TL experiments. Our results show that VTs exhibit strong generalization properties and that these networks are more powerful feature extractors than CNNs.作者: Optimum 時(shí)間: 2025-3-27 19:28
Asynchronous Kalman Filter for?Event-Based Star Trackingchronously to update a Kalman filter that estimates star position and velocity in an image. The proposed tracking method is validated on real and simulated data and shows state-of-that-art tracking performance against existing approach.作者: 無(wú)能力之人 時(shí)間: 2025-3-28 01:22 作者: 龍卷風(fēng) 時(shí)間: 2025-3-28 05:16 作者: 騷動(dòng) 時(shí)間: 2025-3-28 08:01 作者: monologue 時(shí)間: 2025-3-28 14:08 作者: kindred 時(shí)間: 2025-3-28 18:32
MaRF: Representing Mars as?Neural Radiance Fieldsparse set of images. To speed up the learning process, we replaced the sparse set of rover images with their neural graphics primitives (NGPs), a set of vectors of fixed length that are learned to preserve the information of the original images in a significantly smaller size. In the experimental se作者: GUILT 時(shí)間: 2025-3-28 20:04 作者: 別炫耀 時(shí)間: 2025-3-29 00:38
Mixed-Domain Training Improves Multi-mission Terrain Segmentatione to deploy across different Martian rover missions for terrain navigation, by utilizing a mixed-domain training set that ensures feature diversity. Evaluation results of using average pixel accuracy show that a semi-supervised mixed-domain approach improves accuracy compared to single domain traini作者: Control-Group 時(shí)間: 2025-3-29 06:00
CubeSat-CDT: A Cross-Domain Dataset for?6-DoF Trajectory Estimation of?a?Symmetric Spacecraftted to the space of camera poses while preserving temporal information. Our results highlight the importance of addressing the domain gap problem to propose reliable solutions for close-range autonomous relative navigation between spacecrafts. Since the nature of the data used during training impact作者: 溫和女孩 時(shí)間: 2025-3-29 10:28
Data Lifecycle Management in?Evolving Input Distributions for?Learning-based Aerospace Applicationsmation gain from an input using Bayesian uncertainty quantification and choosing a subset that maximizes collective information gain using concepts from batch active learning. We show that our algorithm outperforms others on the benchmark, e.g., achieves comparable performance to an algorithm that l作者: BRIBE 時(shí)間: 2025-3-29 12:51 作者: 圖畫文字 時(shí)間: 2025-3-29 18:14 作者: Isthmus 時(shí)間: 2025-3-29 20:46 作者: 假裝是我 時(shí)間: 2025-3-30 00:00
On-the-Go Reflectance Transformation Imaging with?Ordinary Smartphonesunt of data, we propose a neural relighting model that reconstructs object appearance for arbitrary light directions from extremely compact reflectance distribution data compressed via Principal Components Analysis (PCA). Experiments shows that the proposed technique can be easily performed on the f作者: 木訥 時(shí)間: 2025-3-30 04:44
Conference proceedings 2023ng for Next-Generation Industry-LevelAutonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for 作者: 惡臭 時(shí)間: 2025-3-30 09:35
Arthur N. Popper,Anthony Hawkinsparse set of images. To speed up the learning process, we replaced the sparse set of rover images with their neural graphics primitives (NGPs), a set of vectors of fixed length that are learned to preserve the information of the original images in a significantly smaller size. In the experimental se作者: MOT 時(shí)間: 2025-3-30 14:42 作者: PIZZA 時(shí)間: 2025-3-30 18:56 作者: 擔(dān)心 時(shí)間: 2025-3-30 22:17
Robert J. McMahon,Ray DeV. Petersted to the space of camera poses while preserving temporal information. Our results highlight the importance of addressing the domain gap problem to propose reliable solutions for close-range autonomous relative navigation between spacecrafts. Since the nature of the data used during training impact作者: 控制 時(shí)間: 2025-3-31 03:50
Robert J. McMahon,Ray DeV. Petersmation gain from an input using Bayesian uncertainty quantification and choosing a subset that maximizes collective information gain using concepts from batch active learning. We show that our algorithm outperforms others on the benchmark, e.g., achieves comparable performance to an algorithm that l作者: 和諧 時(shí)間: 2025-3-31 05:28
Familial Factors and Substance Use Disordersth this promising preliminary result, we believe the ViT (or attention-based) network architecture can be an important tool for strong lensing science for the next generation of surveys. The open source of our code and data is in ..作者: 安心地散步 時(shí)間: 2025-3-31 10:17
https://doi.org/10.1007/978-981-99-6335-5ults in pairs that are falsely considered as negatives, impacting training performance. In this study, we propose two approaches to resolve this: 1) an unsupervised deep clustering step on the Mars datasets, which identifies clusters of images containing similar semantic content and corrects false n作者: Optic-Disk 時(shí)間: 2025-3-31 15:55 作者: 壟斷 時(shí)間: 2025-3-31 19:16 作者: LEER 時(shí)間: 2025-3-31 23:47 作者: prostate-gland 時(shí)間: 2025-4-1 04:10
Transfer Learning for?On-Orbit Ship Segmentationr space-based EO systems. Since the development of on-orbit AI applications requires rarely available raw data, training of these AI networks remains a challenge. To address this issue, we investigate the effects of varying two key image parameters between training and testing data on a ship segment作者: ethereal 時(shí)間: 2025-4-1 08:06
