A method for clustering based on unsupervised learning according to an embodiment of the invention enables clustering for newly generated patterns and is robust against noise, and does not require tagging for training data. According to one or more embodiments of the invention, noise is accurately removed using three-dimensional stacked spatial auto-correlation, and multivariate spatial probability distribution values and polar coordinate system spatial probability distribution values are used as learning features for clustering model generation, making them robust to noise, rotation, and fine unusual shapes. In addition, clusters resulting from clustering are classified into multi-level clusters, and stochastic automatic evaluation of normal/defect clusters is possible only with measurement data without a label.

A method of barrier detection in an imaging controller includes: obtaining an image of a support structure configured to support a plurality of items on a support surface extending between a shelf edge and a shelf back; extracting frequency components representing pixels of the image; based on the extracted frequency components, identifying a barrier region of the image, the barrier region containing a barrier adjacent to the shelf edge; and detecting at least one empty sub-region within the barrier region, wherein the empty sub-region is free of items between the barrier and the shelf back.

A method may include obtaining an image including a face. The method may further include determining at least one time domain feature related to the face in the image and at least one frequency domain information related to the face in the image. The method may further include evaluating the quality of the image based on the at least one time domain feature and the frequency domain information.

A computer implemented method and apparatus for a marine vessel data system, the method comprising: receiving data from at least one sensor configured to measure vibration and operationally arranged to the marine vessel to provide time-domain reference sensor data; maintaining the time-domain reference sensor data within a data storage system; generating a Fast Fourier Transform (FFT) on the time-domain reference sensor data to provide a plurality of reference spectra files in frequency-domain, wherein each reference spectra file comprises spectra data defined by amplitude information and frequency information, and each spectra file is associated with condition information determined based on collection of the time-domain reference sensor data; normalizing each reference spectra file by converting the frequency information to order information using the condition information to provide normalized reference spectra files; and training a convolutional autoencoder type of neural network using the normalized reference spectra files.

A system that measures the motion of a platform traveling over water by reference to images taken from the platform. In one embodiment, the invention is comprised of a computer connected to a camera and an Inertial Measurement Unit (IMU) which provides estimates of the platform's location, attitude and velocity by integrating the motion of the platform with respect to features on the water's surface, corrected for the motion of those features. The invention measures the motion of the water features according to equations of surface water wave celerity to measure motion of features across the water, and by measuring the feature motion shear across images or the discrepancy between the navigation estimates and the observed water feature motion to detect boundaries of water currents. The invention is also capable of measuring water depth, wave motion, sea state and current present in the water, whether affixed to a navigating platform or to a stationary reference point.

This application provides a target tracking method, including: obtaining a plurality of consecutive picture frames of a target video, and setting a tracked target region of an n.sup.th picture frame; performing a feature extraction operation on the tracked target region of the n.sup.th picture frame, to obtain a feature map of the tracked target region; calculating a weighted filter corresponding to the input feature map according to a correlation filter algorithm and a mean pooling constraint condition; calculating an output response of an (n+1).sup.th picture frame by using the weighted filter and an input feature map of the (n+1).sup.th picture frame in the plurality of consecutive picture frames, and determining a tracked target region of the (n+1).sup.th picture frame according to the output response of the (n+1).sup.th picture frame, until tracked target regions of all the consecutive picture frames are obtained. This application improves precision and effectiveness of target tracking.

A number-of-occupants detection system (1) includes an image correction unit (120) that generates a corrected image based on an image generated by an imaging unit (110) that images a vehicle traveling on a road having a plurality of lanes by executing correction processing on the image for reducing blurring of a subject captured in the image using a parameter according to a position where the vehicle travels, and a count unit (130) that counts the number of occupants of the vehicle using the corrected image generated by the image correction unit (120).

Various embodiments of the present disclosure provide systems and methods for classifying and evaluating an electronic object based at least in part on terahertz (THz) data. THz data may comprise time-domain THz data collected via THz time domain spectroscopy of the electronic object. THz data may further comprise frequency-domain THz data, which may be generated based at least in part on the time-domain THz data. A unique THz fingerprint may be generated for the electronic object based at least in part on the THz data. This unique THz fingerprint may be compared to an earlier generated THz fingerprint of the same electronic object to evaluate reliability and consistency. The unique THz fingerprint may also be compared to THz fingerprints or THz data of other electronic objects of the same object type, class, design, and/or the like, to validate the electronic object (e.g., determine if the electronic object is counterfeit).

An information processing device for processing a signal with a neural network includes: a Fourier transform layer for performing Fourier transform on an input signal and outputting a first amplitude signal and a first phase signal; an amplitude connection layer for multiplying the first amplitude signal by a first weight matrix for which a value is to be updated through training, and outputting a second amplitude signal; a phase connection layer for multiplying the first phase signal by a second weight matrix for which a value is to be updated through training, and outputting a second phase signal; a complex activation layer for updating at least the second amplitude signal, of the second amplitude signal and the second phase signal, using a complex activation function f in a spatial frequency domain; and an inverse Fourier transform layer for combining the updated signals and performing inverse Fourier transform thereon.

Disclosed are methods, systems, and non-transitory computer-readable medium for color and pattern analysis of images including wearable items. For example, a method may include receiving an image depicting a wearable item, identifying the wearable item within the image by identifying a face of an individual wearing the wearable item or segmenting a foreground silhouette of the wearable item from background image portions of the image, determining a portion of the wearable item identified within the image as being a patch portion representative of the wearable item depicted within the image, deriving one or more patterns of the wearable item based on image analysis of the determined patch portion of the image, deriving one or more colors of the wearable item based on image analysis of the determined patch portion of the image, and transmitting information regarding the derived one or more colors and information regarding the derived one or more patterns.