71 results about "Simple Features" patented technology

The aesthetic quality of a picture is automatically inferred using visual content as a machine learning problem using, for example, a peer-rated, on-line photo sharing Website as data source. Certain visual features of images are extracted based on the intuition that they can discriminate between aesthetically pleasing and displeasing images. A one-dimensional support vector machine is used to identify features that have noticeable correlation with the community-based aesthetics ratings. Automated classifiers are constructed using the support vector machines and classification trees, with a simple feature selection heuristic being applied to eliminate irrelevant features. Linear regression on polynomial terms of the features is also applied to infer numerical aesthetics ratings.

The embodiment of the invention discloses a video classification method and device, a model training method and device, equipment and a storage medium, and belongs to the technical field of computer vision. The method comprises the following steps: acquiring a video; selecting n image frames from the video; extracting respective feature information of the n image frames through a feature extraction network according to a learned feature fusion strategy; and determining a video classification result according to respective feature information of the n image frames. According to the learned feature fusion strategy, feature information of the image frame is extracted; wherein the feature fusion strategy indicates that each image frame is fused with feature information of other image frames; the proportion of the feature information of each image frame is determined, the classification result of the video is determined according to the feature information of the image frames, the feature fusion strategy replaces complex and repeated 3D convolution operation through simple feature information fusion, the workload is small, the time for finally obtaining the classification result of thevideo is short, and the efficiency is high.

The described systems and methods are directed at converting a file with complex elements so that a legacy utilization device, such as a legacy printer, can properly process the file. The described systems may include a converter module with a modular filter pipeline. The converter module may identify elements with complex features in a file. Simpler features that approximate the complex features are determined. The identified elements in the file may be replaced with elements having the simpler features.

A device and method for preservation of an oxidizable substance, e.g. a liquid such as a beverage of which wine is an example, is described. In a first aspect, a device is described for controlling the delivery of a predetermined amount of inert gas into a container with a single opening such as a wine bottle at a pre-determined pressure, suitable for an efficient delivery of the inert gas, with a simultaneous displacement of the air present in the top space of the container or bottle, in a simple actuation. In a second aspect, an improved container or bottle stopper is described with simple features that allow easy and cheap manufacture significantly reducing the cost of the stopper. In a third aspect to an efficient and cost-effective method is described for the preservation of a degradable substances especially liquids such as beverages of which wine is an example.

The present approach relates, in some aspects, to a multi-level and a multi-channel frame work for segmentation using model-based or “shallow” classification (i.e. learning processes such as linear regression, clustering, support vector machines, and so forth) followed by deep learning. This framework starts with a very low resolution version of the multi-channel data and constructs an shallow classifier with simple features to generate a coarser level tissue mask that in turn is used to crop patches from the high-resolution volume. The cropped volume is then processed using the trained convolution network to perform a deep learning based segmentation within the slices.

The invention discloses a back-bolt type stone curtain wall, which comprises a crossbeam, and a connector is fixedly connected to the beam. The connector is an L-shaped structure. Bolts are attached to the stone. The back-bolt type stone curtain wall has the characteristics of convenient and simple installation, and it will not damage the stone panel, and has a simple structure and is easy to realize.