Abstract: A method and an apparatus for equipment anomaly detection are provided. In the method, multiple signals of an equipment during normal operation or appearance images of the equipment when an appearance is not damaged are acquired in advance by using a data acquisition device to train a machine learning model stored in a storage device. A real-time signal of the equipment during a current operation or a current image of the appearance of the equipment is acquired by using the data acquisition device, and input to the trained machine learning model to output a detection result indicating a current operation state of the equipment or a current state of the appearance of the equipment.

Abstract: A classification device and a classification method based on a neural network are provided. A heterogeneous integration module includes a convolutional layer, a data normalization layer, a connected layer and a classification layer. The convolutional layer generates a first feature map according to a first image data. The data normalization layer normalizes a first numerical data to generate a first normalized numerical data. The first numerical data corresponds to the first image data. The connected layer generates a first feature vector according to the first feature map and the first normalized numerical data. The classification layer generates a first classification result corresponding to a first time point according to the first feature vector. The heterogeneous integration module generates a second classification result corresponding to a second time point.

Abstract: A board defect filtering method is provided. The method includes: receiving a defect list; obtaining a plurality of defect images of a plurality of defect records on the defect list; receiving a circuit layout image; analyzing a defect location of a first defect image of the plurality of defect images according to the circuit layout image; cropping the first defect image to obtain a first cropped defect image according to the defect location; inputting the first cropping defect image to a defect classifying model; and determining whether the first defect image is a qualified product image or not according to an output result of the defect classifying model.

Abstract: A board defect filtering method is provided. The method includes: receiving a defect list; obtaining a plurality of defect images of a plurality of defect records on the defect list; receiving a circuit layout image; analyzing a defect location of a first defect image of the plurality of defect images according to the circuit layout image; cropping the first defect image to obtain a first cropped defect image according to the defect location; inputting the first cropping defect image to a defect classifying model; and determining whether the first defect image is a qualified product image or not according to an output result of the defect classifying model.

Abstract: According to embodiments of the disclosure, an optical inspection system and an optical inspection method thereof are provided. The optical inspection system may include a lens group, a light source and a lens controlling module. The light source is configured to illuminate an object. The lens group is configured to project the light from the light source as a collimated rectangular shaped light. The lens controlling module is configured to switch the lens group for changing an irradiance of the collimated rectangular shaped light and adjusting an illuminated area of the collimated rectangular shaped light on an object surface of the object.

Abstract: This disclosure provides an image composition system and its method. The system includes: an image capturing unit configured for capturing at least one first image of a real object; a depth information generating unit disposed on the image capturing unit and configured for measuring a depth information between the depth information generating unit and the real object; a computing unit receiving the at least one first image and the depth information, performing the computation of removing a noise caused by a moving object other than the real object from the received depth information, and computing a moving trajectory of the image capturing unit; and a composition unit compositing the at least one first image and a second image of a virtual scene, and display the composited result on a display unit.

Abstract: A stereo camera apparatus including an image capturing device, an optical axis controlling module and a calculating module is provided. The image capturing device is suitable for obtaining a stereo image, and the image capturing device includes a plurality of image capturing units. The optical axis controlling module is coupled to the image capturing device. The calculating module is coupled to the image capturing device and the optical axis controlling module, wherein the calculating module calculates a calibration condition according to the stereo image. The optical axis controlling module adjusts directions of imaging optical axes of the image capturing units. After being adjusted by the optical axis controlling modules, the imaging optical axes of the image capturing units are aligned. Besides, a self-calibration apparatus and a method of calibration are also provided.

Abstract: This disclosure provides an image composition system and its method. The system includes: an image capturing unit configured for capturing at least one first image of a real object; a depth information generating unit disposed on the image capturing unit and configured for measuring a depth information between the depth information generating unit and the real object; a computing unit receiving the at least one first image and the depth information, performing the computation of removing a noise caused by a moving object other than the real object from the received depth information, and computing a moving trajectory of the image capturing unit; and a composition unit compositing the at least one first image and a second image of a virtual scene, and display the composited result on a display unit.

Abstract: A stereo camera apparatus including an image capturing device, an optical axis controlling module and a calculating module is provided. The image capturing device is suitable for obtaining a stereo image, and the image capturing device includes a plurality of image capturing units. The optical axis controlling module is coupled to the image capturing device. The calculating module is coupled to the image capturing device and the optical axis controlling module, wherein the calculating module calculates a calibration condition according to the stereo image. The optical axis controlling module adjusts directions of imaging optical axes of the image capturing units. After being adjusted by the optical axis controlling modules, the imaging optical axes of the image capturing units are aligned. Besides, a self-calibration apparatus and a method of calibration are also provided.