Abstract:
An electronic device is described. The electronic device includes a memory and a processor in communication with the memory. The processor is configured to receive an image. The processor is also configured to extract a lane response map from the image. The processor is further configured to estimate one or more lane markers based on the lane response map.
Abstract:
A method, which is performed by an electronic device, for resizing an image having text is disclosed. The method may include determining layout information of at least one text region in the image. The layout information may include at least one of a number, a size, a location, a shape, or a text density of the at least one text region in the image. The method may also select a seam carving operation, a cropping operation, or a scaling operation for the image based on the layout information, a size of the image, and a target image size. The selected operation may be performed to resize the image to the target image size based at least on one of the layout information, the size of the image, or the target image size. The resized image may include the at least one text region.
Abstract:
A method, performed by an electronic device, for identifying a language of text in an image of an object is disclosed. In this method, the image of the object is received. The method includes detecting a text region in the image that includes the text and identifying a script of the text in the text region that is associated with a plurality of languages. Based on the plurality of languages associated with the script, the language for the text is determined.
Abstract:
Disclosed are techniques for performing lane instance recognition. Lane instances are difficult to recognize since they are long and elongated, and they also look different from view to view. An approach is proposed in which local mask segmentation lane estimation and global control points lane estimation are combined.
Abstract:
Certain aspects of the present disclosure are directed to methods and apparatus for deep learning in an artificial neural network. One example method generally includes receiving input data at an input to a layer of the neural network; replicating a group of neural processing units in the layer to form a superset of neural processing units, the superset comprising n instances of the group of neural processing units; processing the input data using the superset to generate output data for the layer; and determining an uncertainty of the output data. Processing the input data includes performing a dropout function by zeroing out one or more weights of a set of weights for each of the n instances of the superset of neural processing units and convolving, for each of the n instances in parallel, the input data with one or more non-zeroed out weights of the set of weights.
Abstract:
A method, which is performed by an electronic device, for resizing an image having text is disclosed. The method may include determining layout information of at least one text region in the image. The layout information may include at least one of a number, a size, a location, a shape, or a text density of the at least one text region in the image. The method may also select a seam carving operation, a cropping operation, or a scaling operation for the image based on the layout information, a size of the image, and a target image size. The selected operation may be performed to resize the image to the target image size based at least on one of the layout information, the size of the image, or the target image size. The resized image may include the at least one text region.
Abstract:
A method, performed by an electronic device, for verifying a user to allow access to the electronic device is disclosed. In this method, sensor data may be received from a plurality of sensors including at least an image sensor and a sound sensor. Context information of the electronic device may be determined based on the sensor data and at least one verification unit may be selected from a plurality of verification units based on the context information. Based on the sensor data from at least one of the image sensor or the sound sensor, the at least one selected verification unit may calculate at least one verification value. The method may determine whether to allow the user to access the electronic device based on the at least one verification value and the context information.
Abstract:
A method, performed by an electronic device, for linking a thumbnail of an image and at least one web page is disclosed. In this method, the image including at least one text region may be accessed in a storage unit. At least one text region may be detected in the image and at least one character string in the at least one text region may be recognized. Further, the method may include selecting the at least one web page from the plurality of web pages and linking the thumbnail of the image and the at least one web page.
Abstract:
A method, which is performed by an electronic device, of automatically activating a flash for an image sensor of the electronic device is disclosed. The method may include receiving a first image including at least one text region and determining feature data characterizing the at least one text region in the first image. The method may also identify at least one candidate specular reflection region in the first image. Based on the feature data and the at least one candidate specular reflection region, the flash may be activated. Upon activating the flash, a second image including the at least one text region may be captured.
Abstract:
A mobile wireless device detects a first wireless device that seems to be a known access point. Location-specific contextual information for the first wireless device is identified. A wireless connection with the first wireless device is established if it is determined that the location-specific contextual information for the first wireless device matches known location-specific contextual information for the access point. A wireless connection with the first wireless device is not established, or is only established after receiving user confirmation, if it is determined that the location-specific contextual information for the first wireless device does not match the known location-specific contextual information for the access point.