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《中国图象图形学报》大模型在航空领域的智慧赋能专栏简介
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张艳宁 1 , 张磊 1 , 董晶 2 , 王明波 3 , 闫庆森 1 , 丁晨 4 , 曹聪琦 1 , 赵席彬 5, *
中国图象图形学报 | 大模型在航空领域的智慧赋能 2026,31(9): 3075-3076
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中国图象图形学报 |大模型在航空领域的智慧赋能 2026 , 31 (9) : 3075 -3076
《中国图象图形学报》大模型在航空领域的智慧赋能专栏简介
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张艳宁1, 张磊1, 董晶2, 王明波3, 闫庆森1, 丁晨4, 曹聪琦1, 赵席彬5, *
作者信息
  • 1 西北工业大学,西安 710129
  • 2 中国科学院自动化研究所,北京 100190
  • 3 中国航空工业集团公司西安航空计算技术 研究所,西安 710065
  • 4 西安邮电大学,西安 710121
  • 5 《中国图象图形学报》编辑部,北京 100190
通讯作者:
赵席彬
Affiliations
出版时间: 2026-09-16 doi: 10.11834/jig.2600009
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张艳宁, 张磊, 董晶, 王明波, 闫庆森, 丁晨, 曹聪琦, 赵席彬. 《中国图象图形学报》大模型在航空领域的智慧赋能专栏简介. 中国图象图形学报, 2026 , 31 (9) : 3075 -3076 . DOI: 10.11834/jig.2600009
. Journal of Image and Graphics, 2026 , 31 (9) : 3075 -3076 . DOI: 10.11834/jig.2600009
随着人工智能技术的迅猛发展,大模型已成为驱动航空领域技术变革的关键,是我国推动航空产业智能化转型升级的战略支点。以视觉基础模型、多模态大模型为代表的新一代人工智能技术,正在重塑航空系统的感知、认知、决策与控制方式。在航空制造环节,大模型为智能设计与缺陷检测提供了新范式;在航空遥感领域,多模态大模型提升了多源异构数据的解译精度与效率,推动智能解译向开放词汇、跨模态推理演进;在航空安全方面,大模型驱动的态势感知与辅助决策为飞行安全提供了更可靠的保障。
在中国科协年会支持下,中国图像图形学会联合《中国图象图形学报》组织"大模型在航空领域的智慧赋能"专题,围绕大模型赋能航空制造、航空遥感、航空安全及人机协同等方向征文,并邀业内专家策划推出同名专栏。本专栏兼具理论意义与工程价值:推动航空智能信息处理理论体系完善与新型算法突破,并梳理典型场景与工程实践,加速成果向真实场景转化。
专栏收到领域内学者积极投稿。经严格评审,共收录学术论文13篇,其中综述9篇、算法论文4篇。
《大模型赋能下的航空图像复原技术研究进展》(作者:郑萌萌,郭宸瑞*,张磊,魏巍)针对航空图像噪声、模糊、低光及多退化耦合,梳理单一与多退化联合建模脉络,从视觉基础模型、多模态大模型及智能体三类方法分析驱动复原技术,归纳多退化耦合建模、语义信息利用等挑战。
《航空光谱图像智能处理:方法、应用与挑战》(作者:赵兴兵,郭宸瑞,李羽珊,张磊*,魏巍)针对航空光谱数据高维、强相关、噪声复杂等特点,梳理光谱—空间特征提取、分类、检测、变化检测及光谱解混关键技术,总结其在精准农业、环境灾害监测的应用,剖析数据稀缺与空天地协同困难,展望遥感基础模型、自监督学习与空天地一体化协同。
《航空遥感场景跨域少样本目标检测进展研究》(作者:陈布衣,郭宸瑞*,单淳,张磊,魏巍)针对航空遥感中标注样本稀缺与域间分布差异并存的难题,梳理跨域少样本目标检测的任务边界与域偏移,从迁移与域对齐、元学习、生成式增强、视觉语言对齐及大模型五类方法综述。
《多模态信息融合研究进展》(作者:胡玉梅*,王晓华,邓豹,赵洋洋,赵艺阳)梳理从早期、晚期到混合融合的演进脉络,阐述基于注意力的交互建模、基于对比学习的语义对齐及以大语言模型为载体的生成式融合三方式,探讨其在战场态势感知与无人系统协同中的应用。
《开放词汇语义分割研究进展》(作者:刘明怡,谢国森*,舒祥波,张磊)围绕突破闭集语义分割对固定类别集合的依赖展开,指出以CLIP为代表的视觉—语言预训练模型侧重图像级语义对齐、难满足像素级密集预测需求;进而沿零样本分割、图文监督、双阶段和单阶段方法等路线归纳代表性方法的思想与局限。
《面向无人机的多模态视觉理解大模型研究进展》(作者:余雅婷,曹聪琦*,王昭颖,张艳宁)构建“基础感知—语义推理—决策规划”三层能力框架,归纳基础目标感知、事件语义分析与飞行决策规划等任务;回顾从视觉基础模型感知建模到大语言模型与多模态大模型语义推理、再到具身视觉—语言—行动模型决策规划的演进路径。
《具身智能视角下无人机视觉语言导航研究进展》(作者:郑周一,郭宸瑞,单淳,张磊*,魏巍)围绕无人机据自然语言指令在非结构化三维环境自主导航这一空中具身智能方向,归纳三类仿真平台特点并对比主流数据集差异;从感知表征、推理范式、记忆存储和具身控制四模块剖析跨模态对齐、大模型推理与长程记忆等关键技术。
《人工智能辅助的单机长飞行驾驶技术综述》(作者:袁林,李阳,苗延飞,李枭扬,曹聪琦*)围绕单机长体制中填补副驾驶认知与决策空缺这一核心瓶颈,构建"感知—认知—推理—交互决策—安全监控"系统分析框架,阐述基于脑电图、功能性近红外光谱与计算机视觉的多模态生理行为感知技术,归纳大模型与深度强化学习协同的智能航路规划方法。
《大模型赋能航空遥感智能解译的进展与思考》(作者:郎晋伟*,李娅星,刘帅,康晓东,程俊强)指出传统解译依赖单源传感器与单任务学习模型、难应对目标尺度多变、时空异质性强的复杂场景,重点讨论跨传感器多尺度融合、空间语义推理与模型可解释性评估。
《时间差引导的高光谱图像变化检测网络》(作者:丁晨*,张景博,郝小锋,郑思睿,闫松)针对现有方法难充分利用多层级时间差异信息,提出TDG-Net:以Vision Mamba为主干构建孪生架构,设计时间存储器模块提取显式时间差特征,并通过时域差引导策略转化为空间注意力权重反馈至特征提取网络。
《大模型语义增强的多时相多模态遥感影像匹配方法》(作者:张旺,陈涛,裴根生,李宝晨,韦明韬,姚亚洲*)针对多时相、多模态影像在光谱差异与季节变化下匹配稳定性不足,基于SeCo数据集构建含15000对可见光与近红外跨时相样本的匹配基准,并提出以XoFTR为主干、引入冻结DINOv3提取稠密语义特征的匹配方法。
《双时相特征增强引导的多关系差异耦合遥感变化字幕生成》(作者:于洁潇,付雨杰,刘婧*)针对关键变化区域表征不足、双时相差异关系建模不充分,采用RemoteCLIP-RN50提取双时相影像深层语义特征并自适应强化关键变化区域,构建多关系差异耦合框架对原始特征、绝对差异、乘积交互和相似性信息建模。
《模态可靠性建模的航空遥感可见光—红外目标检测》(作者:余东,张淳杰*,张晓宇,郑晓龙)针对现有方法难随成像条件自适应调节模态贡献,构建面向无人机场景的模态质量属性描述数据集,利用视觉语言模型编码语义先验并引导检测网络学习检测导向的模态可靠性表征,从全局与局部两层面联合建模实现自适应融合。
我们期待广大读者和科技人员通过“大模型在航空领域的智慧赋能”专栏,更深入地了解该领域的最新方法和应用,共同推动大模型与航空领域的深度交叉融合,为我国航空事业发展贡献智慧。
专栏编委会
张艳宁,中国科学院院士,西北工业大学教授,主要研究方向为图像处理、计算机视觉、空间环境探测动态视觉计算理论与技术。
张磊,西北工业大学教授,主要研究方向为计算机视觉、光谱重建、图像超分重建和压缩感知。
董晶,中国科学院自动化研究所研究员,主要研究方向为多媒体取证与安全、网络内容分析和人工智能安全。
王明波,中国航空工业集团公司西安航空计算技术研究所正高级工程师,主要研究方向为航空领域人工智能应用、航空科研设计与生产制造智能化。
闫庆森,西北工业大学教授,主要研究方向为计算机视觉、图像处理、人工智能和机器学习。
丁晨,西安邮电大学副教授,主要研究方向为图像处理、机器学习和模式识别。
曹聪琦,西北工业大学副教授,主要研究方向为计算机视觉、智能视频理解、数据高效学习与时空预测。
专栏责编
赵席彬,编辑,主要研究方向为学术出版和媒体传播等。E-mail:zhaoxibin@aircas.ac.cn。

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2026年第31卷第9期
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doi: 10.11834/jig.2600009
  • 首发时间:2026-10-30
  • 出版时间:2026-09-16
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    1 西北工业大学,西安 710129
    2 中国科学院自动化研究所,北京 100190
    3 中国航空工业集团公司西安航空计算技术 研究所,西安 710065
    4 西安邮电大学,西安 710121
    5 《中国图象图形学报》编辑部,北京 100190

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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