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Imp: Highly Capable Large Multimodal Models for Mobile Devices

IEEE Transactions on Multimedia 2025年 27卷 2961-2974页

作者： Shao, Zhenwei Yu, Zhou Yu, Jun Ouyang, Xuecheng Zheng, Lihao Gai, Zhenbiao Wang, Mingyang Kuang, Zhenzhong Ding, Jiajun Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science Hangzhou310005 China Harbin Institute of Technology Shenzhen Department of Computer Science and Technology Shenzhen China Hangzhou Dianzi University HDU-ITMO Joint Institute Hangzhou310005 China

By harnessing the capabilities of large language models (LLMs), recent large multimodal models (LMMs) have shown remarkable versatility in open-world multimodal understanding. Nevertheless, they are usually parameter-heavy and computation-intensive, thus hindering their applicability in resource-constrained scenarios. To this end, several lightweight LMMs have been proposed successively to maximize the capabilities under constrained scale (e.g., 3B). Despite the encouraging results achieved by these methods, most of them only focus on one or two aspects of the design space, and the key design choices that influence model capability have not yet been thoroughly investigated. In this paper, we conduct a systematic study for lightweight LMMs from the aspects of model architecture, training strategy, and training data. Based on our findings, we obtain Imp - a family of highly capable LMMs at the 2B$\sim$4B scales. Notably, our Imp-3B model steadily outperforms all the existing lightweight LMMs of similar size, and even surpasses the state-of-the-art LMMs at the 13B scale. With low-bit quantization and resolution reduction techniques, our Imp model can be deployed on a Qualcomm Snapdragon 8Gen3 mobile chip with a high inference speed of about 13 tokens/s. © 2025 IEEE.

关键词： Visual languages

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Assessing the Feasibility of Ion Beam-based Asteroid Deflection for Planetary Defense

Assessing the Feasibility of Ion Beam-based Asteroid Deflect...

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AIAA science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Wijayatunga, Minduli C. Buonagura, Carmine Bandyopadhyay, Saptarshi Bhaskaran, Shyamkumar Zhou, Bonan Chodas, Paul Nakka, Yashwanth Kumar Petropoulos, Anastassios Frazier, William Nesnas, Issa Ardito, Steven Fesq, Lorraine Brophy, John Jet Propulsion Laboratory California Institute of Technology Auckland Space Institute University of Auckland 4800 Oak Grove Dr PasadenaCA91109 United States Jet Propulsion Laboratory California Institute of Technology University of Auckland Auckland CBD 34 Princes Street Auckland1010 New Zealand Politecnico di Milano Jet Propulsion Laboratory California Institute of Technology Department of Aerospace Science and Technology Via La Masa 34 Milan20156 Italy Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology Mission Systems and Operations Division 270 Ferst Dr AtlantaGA30332 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The potential threat of asteroid impacts on Earth has prompted significant research into methods for asteroid deflection such as kinetic impactor, gravity tractor, nuclear options and ion beam deflection (iBeam). Among these methods, iBeam is a promising technique as it can achieve significant deflection without the risk of unintended asteroid disruption. In this paper, we analyze the feasibility of iBeam missions for deflecting potentially hazardous asteroids. We first present the architecture for iBeam missions, including the design of the spacecraft and subsystem models, multiple ion-beam plasma plume models, and a dynamics model for the spacecraft-asteroid system. Utilizing these models, we implement closed-loop control for maintaining iBeam spacecraft position relative to the asteroid with a proportional-integralderivative controller and manage attitude using a nonlinear proportional-derivative controller. We then perform Monte Carlo (MC) simulations of complete iBeam missions over various asteroid characteristics to study iBeam efficiency. Through the MC simulations, we study the effect of asteroid diameter (50-100 m), density (2-8 g cm-3), spin axis (principal axis vs minor axis), and shape (spherical vs irregular) on the deflection. Results indicate that under the assumed capabilities of the iBeam spacecraft, successful deflection of 50 m diameter spherical asteroids is achievable within 6 months for densities under 4 g/cm3 or within 5 years for densities below 8 g/cm3. Similarly, for 150 m diameter spherical asteroids, successful deflection within 5 years is possible if densities are under 2 g/cm3. Additionally, the study reveals a marginal influence of spin axis and shape on deflection. Compared to a reference case of a spherical asteroid, a maximum change of 5.6% is observed for irregular-shaped asteroids rotating around their minimum moment of inertia axis pointed towards the spacecraft. © 2025, American Institute of Aeronautics and Astronautics Inc, AIA

关键词： Spheres

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Effect of 20 MeV proton irradiation on the electrical properties of β-Ga2O3 Schottky barrier diodes with field plate

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Applied Physics Letters 2025年第16期126卷

作者： Feng, Yahui Guo, Hongxia Zhang, Jinxin Ouyang, Xiaoping Bai, Ruxue Zheng, Xuefeng Ma, Xiaohua Hao, Yue State Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology Faculty of Integrated Circuit Xidian University Xi'an710071 China The School of Materials Science and Engineering Xiangtan University Xiangtan411105 China National Key Laboratory of Strong Pulse Radiation Simulation and Effect Northwest Institute of Nuclear Technology Xi'an710024 China The School of Space Science and Technology Xidian University Xi'an710071 China

In this Letter, the impact of 20 MeV proton irradiation on β-Ga2O3 Schottky barrier diodes (SBDs) with field plates has been investigated. After proton irradiation with fluences of 2 × 1012 and 5 × 1012 p/cm2, the forward current density (JF) decreased from 294.0 to 250.5 and 192.0 A/cm2, respectively. The turn-on voltage (Von) increased from 0.78 to 0.82 and 0.84 V, as measured by current-voltage (I-V) testing. Capacitance-voltage (C-V) measurements showed that the net carrier concentration in the lightly doped drift region of β-Ga2O3 decreased from 1.95 × 1016 to 1.83 × 1016 and 1.38 × 1016 cm−3 after proton irradiation. Additionally, C-V measurements at different frequencies reveal that capacitance gradually decreases as proton fluence increases, though the frequency has little effect on capacitance. The effect of proton irradiation on β-Ga2O3 SBDs was also characterized using low-frequency noise and x-ray photoelectron spectroscopy. The results indicated that the voltage noise spectral density (Sv) gradually increases with proton fluence and bias voltage before and after irradiation due to the introduction of defects. This study provides an important reference for the reliability assessment of β-Ga2O3 SBDs. © 2025 Author(s).

关键词： Schottky barrier diodes

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A Real-Time, Robust, and Versatile Visual-SLAM Framework Based on Deep Learning Networks

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Zhang, Xiao Dong, Hongbin Zhang, Haoxin Zhu, Xiaozhou Li, Shuaixin Deng, Baosong Harbin Engineering University College of Computer Science and Technology National Engineering Laboratory for E-Government Modeling and Simulation Harbin150009 China Defense Innovation Institute Chinese Academy of Military Science Beijing100850 China Sun Yat-sen University College of Systems Science and Engineering Guangzhou510275 China Intelligent Game and Decision Laboratory Beijing100166 China

In this article, we investigate the paradigm of deep learning techniques to enhance the performance of visual-based simultaneous localization and mapping (vSLAM) systems, particularly in challenging environments. By leveraging deep feature extraction and matching methods, we propose a robust, versatile hybrid visual SLAM framework, Rover-SLAM, aimed at improving adaptability in adverse conditions, such as dynamic lighting conditions, areas with weak textures, and camera jitter. Building on excellent learning-based algorithms of recent years, we designed from scratch a novel system that uses the same feature extraction and matching approaches for all SLAM tasks. Our system supports multiple modes, including monocular, stereo, monocular-inertial, and stereo-inertial configurations, offering flexibility to address diverse real-world scenarios. Through comprehensive experiments conducted on publicly available datasets and self-collected data, we demonstrate the superior performance of our Rover-SLAM system compared to the state-of-the-art (SOTA) approaches. We also conducted an in-depth analysis of the integration of visual SLAM with deep learning methods quantitatively to provide insights for future research endeavors in this domain. The experimental results showcase the system's capability of achieving higher localization accuracy and robust tracking performance. © 1963-2012 IEEE.

关键词： Stereocenters

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CRP2-VCS: Contrast-Oriented Region-based Progressive Probabilistic Visual Cryptography Schemes

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IEEE Transactions on Circuits and systems for Video technology 2025年

作者： Wu, Xiaotian Song, Bofan Fang, Jia Yan, WeiQi Peng, Qing-Yu Jinan University Guangdong Key Laboratory of Data Security and Privacy Preserving College of Cyber Security College of Information Science and Technology Guangzhou China Auckland University of Technology Department of Computer and Information Systems Auckland New Zealand Jinan University Sino-French Joint Laboratory for Astrometry Dynamics and Space Science Guangzhou China

Most visual cryptography schemes (VCSs) are condition-oriented which implies their designs focus on satisfying the contrast and security conditions in VCS. In this paper, we explore a new architecture of VCS: contrast-oriented region-based progressive probabilistic VCS (CRP2-VCS). The term contrast-oriented indicates the optimality of multi-contrast is taken into consideration when producing shadows. First of all, new requirements for CRP2-VCS, described by probabilities, are introduced. As a non-interference requirement is proposed, the secret interference problem in existing region-based progressive VCS can be avoided. Then, a construction of CRP2-VCS based on a multi-contrast-maximizing model is provided. The multi-contrast-maximizing problem is essentially a probabilistic VCS model that fuses region-based sharing, multi-contrast optimization, and general access structure (GAS) together. Finally, a Max-Min based technique is adopted to solve the multi-objective optimization problem. Moreover, to further boost the visual quality, the proposed method is extended to allow employing XOR operation for image recovery. Experimental results and comparisons are demonstrated to show the effectiveness and advantages, such as optimal visual quality, non-expansible shadow and GAS sharing policy, are provided by the proposed technique. © 2025 IEEE.

关键词： contrast optimal region Secret sharing visual cryptography

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A Game-Theoretic Approach for Satellites Beam Scheduling and Power Control in a Mega Hybrid Constellation Spectrum Sharing Scenario

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IEEE Internet of Things Journal 2025年

作者： Li, Wei Jia, Luliang Chen, Yingwu Chen, Quan Yan, Jungang Qi, Nan National University of Defense Technology College of Systems Engineering Changsha China Space Engineering University College of Space Information Beijing China National University of Defense Technology College of Aerospace Science and Engineering Changsha China Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing210016 China

A mega hybrid constellation of Low Earth Orbit (LEO) and Geosynchronous Orbit (GEO) satellites represents a typical architecture for future space networks. However, the emergence of such large constellations exacerbates the shortage of spectrum resources. To address this issue, this paper investigates a hierarchical optimization method for beam scheduling and power control of LEO satellites, aiming to extend the available spectrum by sharing the downlink spectrum of GEO satellites. In the upper-layer optimization, a many-to-one matching game model is constructed to achieve optimal matching of LEO satellite beams and LEO Users (LU). A distributed beam matching learning algorithm (DBMLA) is designed to find a stable matching solution for the model, with the convergence of the algorithm theoretically proven. In the lower-layer optimization, an LEO beam power level optimization game model is developed for discrete LEO beam power levels. This model is demonstrated to be an exact potential game with at least one Nash Equilibrium (NE). To solve this NE, a dynamic power allocation logarithmic learning algorithm (DPALLA) is proposed. simulation results verify that the proposed DBMLA-DPALLA hierarchical optimization scheme effectively balances convergence time and accuracy compared to traditional independent optimization strategies. By leveraging the combined effects of the two optimization strategies, it better mitigates the co-channel interference experienced by GEO satellites and improves the average network satisfaction of the LUs. © 2025 IEEE.

关键词： Cochannel interference

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A Multimodal Cross-domain Segmentation Network of Remote Sensing Imagery With Multilevel Deep Cross-Fusion and Adversarial Domain Adaptation

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Li, Guocheng Xi, Bobo He, Yufei Zheng, Tie Li, Yunsong Xue, Changbin Chinese Academy of Sciences Key Laboratory of Electronics and Information Technology for Space Systems National Space Science Center Beijing100190 China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing100049 China Xidian University State Key Laboratory of Integrated Services Networks School of Telecommunications Engineering Xi’an710071 China Xidian University Guangzhou Institute of Technology Guangdong Guangzhou510000 China Chinese Academy of Sciences National Space Science Center Beijing100190 China Xidian University State Key Laboratory of Integrated Service Networks School of Telecommunications Engineering Xi’an710071 China

Deep learning techniques have recently achieved significant success in semantic segmentation for Earth observation tasks using single-modality data within a specific region. However, such optimal conditions are seldom found in real-world applications, leading to subpar performance and limited generalization of existing models when faced with multimodal cross-domain scenarios. To tackle this issue, we introduce a novel segmentation network for remote sensing imagery (RSI) called MC-Seg, which incorporates multilevel deep cross-fusion and adversarial domain adaptation. The MC-Seg framework begins by performing multilevel deep cross-fusion of multimodal data through a complete feature extraction module and three fusion levels: feature, modal, and layer. This approach ensures the thorough utilization of features from various modalities. Following this, the framework integrates a local-global adversarial domain adaptation module to minimize the domain gap, effectively aligning the source and target domains despite the differences in RSI data representations. Experimental validation on the C2Seg dataset shows that our proposed method outperforms existing state-of-the-art techniques. © 1980-2012 IEEE.

关键词： Semantic Segmentation

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GooDFlight: Goal-Oriented Diffusion Model for Flight Trajectory Prediction

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Yang, Songru Liu, Liqin Chen, Bowen Cheng, Shaoyuan Shi, Zhenwei Zou, Zhengxia Beihang University Department of Aerospace Intelligent Science and Technology School of Astronautics China Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing100191 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Beijing Institute of Space Mechanics and Electricity Beijing100076 China

Flight trajectory prediction is an essential task in the air traffic control field. Previous approaches to this problem usually follow a single-stage or short-term intention-guided prediction paradigm, which suffers from problems such as insufficient trajectory prediction diversity, limited accuracy and interpretability. Different from existing paradigms, in this paper, we present GooDFlight - A Goal-oriented Diffusion Model for Flight trajectory prediction. GooDFlight is a long-term intention-guided, diversity-emphasizing framework that decouples the flight trajectory prediction process into two stages: goal estimation and trajectory prediction. In the first stage, we propose a One-then-all goal estimation method to sufficiently cover the macro-uncertainty in flight patterns and then tailor the interaction-aware joint goal distribution, which extends the flight intention from a single, deterministic ground truth to the empirical intention distribution from the similar experience. In the second stage, we employ a transformer-based diffusion model to generate stochastic flight trajectories conditioned on the intention estimations, modeling the micro-uncertainty in flight operations under each pattern estimated in stage one. In terms of evaluation metrics, existing metrics have difficulties in accurately reflecting the model's ability to handle the natural uncertainty of trajectories. We further propose a simple yet effective Global-local endpoints Variance (GLeV) metric for evaluating the diversity of predicted trajectories under social acceptance. Our proposed method is validated in-depth on TrajAir, a large-scale dataset collected from the real-world air traffic control environment at the Pittsburgh-Butler Regional Airport, a non-towered general aviation airport. The experimental results demonstrate that the proposed method significantly outperforms other methods in terms of both accuracy and diversity with superior interpretability. © 1965-2011 IEEE.

关键词： Stochastic systems

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Dynamic analysis of rigid-flexible coupling spacecraft based on Euler parameters

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Scientific Reports 2025年第1期15卷 1-12页

作者： Ji, Yi Zhang, Huan School of Astronautics Harbin Institute of Technology Harbin 150001 China Frontier Science Center for Interaction between Space Environment and Matter Harbin 150001 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin 150001 China MOE Key Laboratory of Dynamics and Control of Flight Vehicle Beijing Institute of Technology Beijing 100081 China

With the development of aerospace technology, rigid-flexible coupling spacecraft with strong nonlinearity dominates, bringing huge challenges for numerical tools. This paper aims to accurately and quickly analyze the dynamic behavior of rigid-flexible coupling spacecraft. In our work, rigid body and flexible body are both described by Euler parameters for avoiding singular angles. Then, for this type of strong nonlinear dynamic system, the BN-stable method that is unconditionally stable for nonlinear initial value problems proposed by the first author is introduced to solve the transient responses. To keep the accuracy of the numerical rotation matrix, the relation between the angular velocity and Euler parameters, and the constraint in the level of velocity, are introduced to reformulate the original BN-stable method. Through the dynamic analysis for rigid satellite bodies and flexible solar wings, we find that the proposed strategy can effectively simulate the dynamic responses of spacecraft, and compared to the currently popular strategy, our strategy enjoys considerable advantages in accuracy, stability, and dissipation. © The Author(s) 2025.

关键词： BN-stability Dynamic analysis Euler parameters Rigid-flexible coupling Rotation matrix

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Constructing ECOC based on confusion matrix for multiclass learning problems

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science China(Information sciences) 2016年第1期59卷 135-148页

作者： Jindeng ZHOU Yun YANG Mingjie ZHANG Haibo XING Science and Technology on Complex Aviation Systems Simulation Laboratory

In the pattern recognition field, error-correcting output codes(ECOC) are a powerful tool to fuse any number of binary classifiers to model multiclass problems, and the research of encoding based on data is attracting more and more attention. In this paper, we are going to propose a new encoding method for constructing subclass Error-Correcting Output Codes, which was first introduced by Escalera et al. To achieve this goal, we first obtain the correlation between each pair of classes with the help of confusion matrix. Then,we select the most easily separated subclasses for classification by following Fisher's principle. At last, we were able to obtain binary partitions based on subclasses. After finishing this work, a new data-driven coding matrixSubclass ECOC will be achieved. Experimental results on University of California Irvine data sets and three kinds of high resolution range profile data sets with logistic linear classifier and support vector machine as the binary classifiers show that our approach can provide a better performance and the robustness of classification with a little longer but acceptable code length.

关键词： machine learning multiclass classification error correcting output codes subclass partition confusion matrix

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