A data storage device and method for reliable watermarking are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to determine whether a watermarking operation to be performed on the data is to be performed by the controller or by the memory; in response to determining that the watermarking operation is to be performed by the controller, performing the watermarking operation; and in response to determining that the watermarking operation is to be performed by the memory, instruct the memory to perform the watermarking operation. Other embodiments are provided.

This application relates to an image processing method and apparatus, a storage medium, and a computer device. The method includes: obtaining a frequency domain mark image, the frequency domain mark image being obtained by performing frequency domain transformation on a spatial domain mark image; obtaining a transparency parameter configured corresponding to the frequency domain mark image; obtaining target page data; and performing layer superimposition rendering of the frequency domain mark image and the target page data according to the transparency parameter. The solution provided in this application can effectively protect target page data.

A method is provided for watermarking a machine learning model used for object detection. In the method, a first subset of a labeled set of ML training samples is selected. Each of one or more objects in the first subset includes a class label. A pixel pattern is selected to use as a watermark in the first subset of images. The pixel pattern is made partially transparent. A target class label is selected. One or more objects of the first subset of images are relabeled with the target class label. In another embodiment, the class labels are removed from objects in the subset of images instead of relabeling them. Each of the first subset of images is overlaid with the partially transparent and scaled pixel pattern. The ML model is trained with the set of training images and the first subset of images to produce a trained and watermarked ML model.

An information processing device, an information processing method, and an information processing program capable of reducing an information processing amount of an application processor that recognizes a subject from an input image are provided. An information processing device (100) according to the present disclosure includes an acquisition unit (4), a generation unit (7), and an output unit (6). From an imaging unit that captures an image and generates image data, the acquisition unit (4) acquires the image data. The generation unit (7) generates, from the image data acquired by the acquisition unit (4), metadata to assist an application processor that executes processing related to the image. The output unit (6) outputs the metadata generated by the generation unit (7) to the application processor.

A system that has a first computing device and a second computing device communicatively coupled to the first computing device via a network. The system further has a processor on the first computing device operated by a host user and sends an invitation to an invitee user to take a picture of himself/herself. The processor also receives a first photograph from the invitee user and merges the first photograph of the invitee user with a second photograph of the host user creating a merged photograph. The processor also can share the merged photograph with other invitee users or social media.

The present disclosure relates generally to data hiding for retail product packaging and other printed objects such as substrates. One embodiment embeds an information signal in a spot color for printing on various substrates. The spot color is screened, and overprinted with process color tint. The tint is modulated prior to overprinting with optimized signal tweaks. The optimization can include consideration of a detector spectral dependency (e.g., red and/or green illumination). Many other embodiments and combinations are described in the subject patent document.

Content is identified using watermarking and/or other content recognition combined with contextual metadata, which facilitates identification and correlation with other content and metadata when it is posted to a network.

Data is encoded into one or more optically encoded images. The optically encoded images are then inserted as image data into a video sequence - i.e., in video frames. Data are transmitted in-band within the video, via any conceivable video distribution channel or format. The video may be trans-coded as required - because the data are optically encoded, any video processing that even crudely preserves the frame images will preserve the optically encoded data. This scheme of in-band data transfer in video is very robust. A video receiving apparatus receives the video, inspects the image data from video frames in memory, detects optically encoded images in the image data, and decodes the optically encoded images to recover the data. The frames carrying optically encoded images are typically discarded and not rendered to a display. The receiver controls connected equipment, other than a display (e.g., a musical instrument), based on the extracted data.

In one aspect, a method includes identifying a group of multiple content-presentation devices that are tuned to the same channel and that are each scheduled to perform, at a modification start-time, a respective content-modification operation that comprises modifying a modifiable content-segment in connection with an upcoming content-modification opportunity on the channel. The method also includes determining that, after the modification start-time, at least a subgroup of the group of content-presentation devices have detected a mismatch between reference fingerprint data representing the modifiable content-segment and query fingerprint data representing content received by at least the subgroup of content-presentation devices. The method also includes determining that at least the subgroup of content-presentation devices are connected to tuner devices associated with the same content distributor and, in response to determining that at least the subgroup of content-presentation devices are connected to tuner devices associated with the same content distributor, performing an action.

A computer-implemented method for training a neural network providing a digital signature for each image given as input to the neural network. The method includes a first training phase of the neural network with a set of training images and a training algorithm aiming to minimize a first cost function. The method also includes a second training phase including at least one iteration of providing an image originating from said set of training images to said neural network in order to obtain a so-called real signature, generating at least one so-called artificial signature from said real signature, calculating an error based upon said real and artificial signatures, and updating at least one layer of said neural network, based upon said error, in order to minimize a second cost function. A neural network trained by the method and to a method for object re-identification on images implementing the neural network.