| | | | 一、前次募集资金使用情况鉴证报告……………………… | 第 1—2 | 页 | | --- | --- | --- | | 二、前次募集资金使用情况报告……………………………第 | 3—13 | 页 | | 三、附件…………………………………………………… | 第 14—17 | 页 | | （一）本所营业执照复印件……………………………… | 第 14 | 页 | 前次募集资金使用情况鉴证报告 天健审〔2025〕6-527 号 凌云光技术股份有限公司全体股东： 我们鉴证了后附的凌云光技术股份有限公司（以下简称凌云光股份公司）管 理层编制的截至 2025 年 6 月 30 日的《前次募集资金使用情况报告》。 一、对报告使用者和使用目的的限定 本鉴证报告仅供凌云光股份公司向特定对象发行股票使用，不得用作任何其 他目的。我们同意本鉴证报告作为凌云光股份公司向特定对象发行股票的必备文 件，随同其他申报材料一起上报。 二、管理层的责任 凌云光股份公司管理层的责任是提供真实、合法、完整的相关资料，按照中 国证券监督管理委员会《监管规则适用指引——发行类第 7 号》的规定编制《前 次募集资金使用情况报告》 ...

虹软科技（688088.SH）2025 年半年报点评 汽车业务量产驱动增长，AI 眼镜+商拍未来可期 2025 年 08 月 26 日 ➢ 事件：近日，虹软科技发布 2025 年半年度报告。2025 年上半年，公司实 现营业收入 4.10 亿元，同比增长 7.73%，归母净利润 0.89 亿元，同比增长 44.06%；其中 Q2 实现营收 2.01 亿元，同比增长 2.08%，归母净利润 0.39 亿 元，同比增长 42.42%。 ➢ 风险提示：生成式 AI 商业化落地有不确定性，行业竞争加剧。 [盈利预测与财务指标 Table_Forcast] ➢ 移动智能终端：Turbo Fusion 稳定续航能力增强，AI 眼镜头部地位巩固。 2025 年上半年，公司移动智能终端视觉解决方案实现收入 3.39 亿元，同比增长 2.23%。智能手机领域，公司针对不同算力芯片平台持续下沉 Turbo Fusion 技 术和扩大产品支持范围，进一步提升了影像处理效率并降低系统负载与功耗，确 保不同平台机型高频使用影像功能时的稳定续航，在夜景、逆光、长焦等场景上 显著改善了画质。AI 眼镜领域，公司重点围绕产品能力提升、生态资 ...

"视觉市场目前已经进入瓶颈期，产业竞争聚焦于降低成本。但是从技术上，对特定场景的定制化是不 足的，缺乏成熟设备快速采集高维信号，如三维、高光谱等更高维的数据。"「西湖智能」创始人袁鑫 博士指出。 袁鑫博士是西湖大学工学院感知与计算成像实验室负责人、博士生导师，是国际计算成像领域权威专 家。因其在单曝光压缩计算成像（Snapshot Compressive Imaging）领域的开创性贡献，于2025年入选美 国光学学会会士（Optica Fellow）。他同时是国家海外高层次青年人才、浙江省高层次人才、浙江省杰 青获得者，并入选斯坦福全球前2%顶尖科学家"终身科学影响力排行榜"。袁博士拥有香港理工大学博 士学位、美国杜克大学博士后经历，并曾担任美国贝尔实验室视频分析与编码首席研究员。截至目前， 其发表学术论文近300篇，谷歌学术引用超13000次，H指数59；申请专利30余项（已授权15项），多项 专利已成功实现产业转化；并担任多个顶级国际期刊编委。 文｜本子 编辑｜廖尧 36氪广东获悉，国内计算成像领域领军企业、高光谱成像设备创新者西湖智能视觉科技（杭州）有限公 司（下称「西湖智能」）近日宣布完成超五千万元 ...

Core Viewpoint - The article discusses a significant breakthrough in industrial anomaly detection through the introduction of the Real-IAD D³ dataset and a novel multi-modal fusion detection method called D³M, which enhances detection performance by integrating various data types [1][11][12]. Group 1: Dataset Overview - The Real-IAD D³ dataset was developed to address limitations in existing anomaly detection methods, providing a comprehensive resource that includes high-resolution RGB images, pseudo 3D photometric images, and micron-level precision 3D point cloud data [3][4]. - The dataset encompasses 20 industrial product categories and 69 defect types, totaling 8,450 samples, with 5,000 normal samples and 3,450 abnormal samples [4]. - Real-IAD D³ significantly outperforms existing datasets like MVTec 3D-AD and Real3D-AD in terms of data scale, defect diversity, and point cloud precision, achieving a point cloud precision of 0.002 mm compared to 0.11 mm and 0.011-0.015 mm for the others [4]. Group 2: Methodology and Performance - The D³M method leverages the Real-IAD D³ dataset by integrating RGB, point cloud, and pseudo 3D depth information, which enhances the performance of anomaly detection [6][11]. - Experimental results indicate that D³M outperforms single and dual-modal methods in both image-level and pixel-level anomaly detection metrics, underscoring the importance of multi-modal fusion in industrial anomaly detection [6][8]. - A comparative analysis of different modality combinations shows that D³M achieves the highest detection accuracy, validating the effectiveness of the multi-modal approach [8][9]. Group 3: Implications and Future Directions - The research is expected to advance the field of industrial anomaly detection, providing more reliable solutions for quality control in manufacturing [12]. - This study is part of the Real-IAD series, with the first work also being recognized at CVPR 2024, indicating ongoing contributions to the field [13].

Investment Rating - The report maintains a "Buy" rating for the company, expecting a price increase of over 15% in the next 6-12 months [5][13]. Core Insights - In 2024, the company achieved revenue of 815 million RMB, a year-on-year increase of 21.6%, and a net profit attributable to shareholders of 177 million RMB, up 99.7% year-on-year [2]. - For Q1 2025, the company reported revenue of 209 million RMB, a 13.8% increase year-on-year, and a net profit of 50 million RMB, reflecting a 45.4% year-on-year growth [2]. - The mobile intelligent terminal visual solutions segment generated revenue of 675 million RMB in 2024, growing 16.2% year-on-year, while the smart driving and other IoT intelligent devices visual solutions segment saw revenue of 127 million RMB, up 71.2% year-on-year [3]. - The company has successfully penetrated the market with its Turbo Fusion technology across various smartphone models, including mid-range and low-end devices, and has launched the first domestic AI glasses [3][4]. Financial Performance - Revenue projections for 2025-2027 are 992 million RMB, 1.218 billion RMB, and 1.5 billion RMB, with year-on-year growth rates of 21.74%, 22.77%, and 23.15% respectively [5][10]. - The net profit forecasts for the same period are 220 million RMB, 270 million RMB, and 339 million RMB, with growth rates of 24.54%, 22.81%, and 25.62% respectively [5][10]. - The company’s P/E ratios are projected to be 79.24, 64.52, and 51.36 for 2025, 2026, and 2027 respectively [5][10].