The CYGNO experiment employs an optical-readout Time Projection Chamber (TPC) to search for rare low-energy interactions using finely resolved scintillation images. While the optical readout provides rich topological information, it produces large, sparse megapixel images that challenge real-time triggering, data reduction, and background discrimination. We summarize two complementary machine-learning approaches developed within CYGNO. First, we present a fast and fully unsupervised strategy for online data reduction based on reconstruction-based anomaly detection. A convolutional autoencoder trained exclusively on pedestal images (i.e. frames acquired with GEM amplification disabled) learns the detector noise morphology and highlights particle-induced structures through localized reconstruction residuals, from which compact Regions of Interest (ROIs) are extracted. On real prototype data, the selected configuration retains (93.0 +/- 0.2)% of reconstructed signal intensity while discarding (97.8 +/- 0.1)% of the image area, with ~25 ms per-frame inference time on a consumer GPU. Second, we report a weakly supervised application of the Classification Without Labels (CWoLa) framework to data acquired with an Americium--Beryllium neutron source. Using only mixed AmBe and standard datasets (no event-level labels), a convolutional classifier learns to identify nuclear-recoil-like topologies. The achieved performance approaches the theoretical limit imposed by the mixture composition and isolates a high-score population with compact, approximately circular morphologies consistent with nuclear recoils.

翻译：CYGNO实验采用光学读出时间投影室（TPC），通过高分辨率闪烁图像探测稀有低能相互作用。虽然光学读出提供了丰富的拓扑信息，但其产生的大规模稀疏百万像素图像对实时触发、数据压缩和本底甄别提出了挑战。本文总结CYGNO实验发展的两种互补机器学习方法。首先，我们提出一种基于重构异常检测的快速全无监督在线数据压缩策略。通过仅使用本底图像（即关闭GEM放大时采集的帧）训练的卷积自编码器，该模型学习探测器噪声形态，并通过局部重构残差突出粒子诱导结构，进而提取紧凑的感兴趣区域（ROIs）。在真实原型数据上，所选配置保留了（93.0 +/- 0.2）%的重构信号强度，同时舍弃（97.7 +/- 0.1）%的图像区域，在消费级GPU上实现约25毫秒的单帧推理时间。其次，我们报告了无标签分类（CWoLa）框架在镅-铍中子源采集数据中的弱监督应用。仅使用混合AmBe数据集与标准数据集（无需事件级标签），卷积分类器成功识别出类核反冲拓扑结构。其性能接近混合物成分设定的理论极限，并能分离出具有紧凑近似圆形形态的高评分事件群，该形态与核反冲特征一致。