G06V10/267

DEEP NEURAL NETWORK-BASED SEQUENCING

A system, a method and a non-transitory computer readable storage medium for base calling are described. The base calling method includes processing through a neural network first image data comprising images of clusters and their surrounding background captured by a sequencing system for one or more sequencing cycles of a sequencing run. The base calling method further includes producing a base call for one or more of the clusters of the one or more sequencing cycles of the sequencing run.

PARAMETER DETERMINATION APPARATUS, PARAMETER DETERMINATION METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM
20230005237 · 2023-01-05 · ·

A detection object analysis unit (4) is a parameter determination apparatus that determines parameters of a plurality of anchor boxes to be used in a sliding window method when a bounding box and a class of an object in an image are detected using a neural network and the sliding window method. The detection object analysis unit (4) includes a distribution generation unit (11) that generates distribution information of parameters of bounding boxes indicated by object specifying information of a plurality of pieces of learning data. The detection object analysis unit (4) includes a clustering processing unit (12) that generates a plurality of clusters by clustering the distribution information. The detection object analysis unit (4) includes a parameter determination unit (13) that determines the parameters of the plurality of anchor boxes based on the plurality of clusters.

OBJECT DETECTION METHOD
20230005293 · 2023-01-05 · ·

An object detection apparatus according to the present invention includes an object detecting unit configured to perform, for each region in an image set based on a size of a specific object detected in the image, a process of detecting the specific object on a new image.

ARTIFICIAL INTELLIGENCE-BASED IMAGE PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE AND STORAGE MEDIUM
20230023585 · 2023-01-26 ·

An artificial intelligence-based image processing method implemented by a computer device is provided. The method includes: acquiring an image; performing element region detection on the image to determine an element region in the image; detecting a target element region in the image using an artificial intelligence-based technique; generating a target element envelope region by searching an envelope for the detected target element region; and fusing the element region and the target element envelope region to obtain a target element region outline.

INFORMATION PROCESSING APPARATUS, LEARNING APPARATUS, IMAGE RECOGNITION APPARATUS, INFORMATION PROCESSING METHOD, LEARNING METHOD, IMAGE RECOGNITION METHOD, AND NON-TRANSITORY-COMPUTER-READABLE STORAGE MEDIUM
20230237777 · 2023-07-27 ·

An information processing apparatus comprises a first generation unit configured to generate a synthesized image in which a second image is synthesized in a closed region in a first image, and a second generation unit configured to generate learning data, the learning data including a label and the synthesized image, the label indicating an object region including a region corresponding to the closed region in the synthesized image.

SEMANTIC ANNOTATION OF SENSOR DATA WITH OVERLAPPING PHYSICAL FEATURES
20230237813 · 2023-07-27 ·

A method for semantic annotation of sensor data may include obtaining sensor data representing an image of a geographic area. The boundary points defining a first polygon in the image of the geographic area may be determined based on the sensor data. An overlap between the first polygon and a second polygon in the image of the geographic area may be detected based at least on the boundary points defining the first polygon. At least one of the first polygon or the second polygon may be modified to remove the overlap between the first polygon and the second polygon. An annotation corresponding to the first polygon may be generated based on the modifying of at least one of the first polygon or the second polygon. The annotation may identify a physical feature within the geographic area. Related systems and computer program products are also provided.

HIERARCHICAL IMAGE GENERATION VIA TRANSFORMER-BASED SEQUENTIAL PATCH SELECTION
20230237709 · 2023-07-27 ·

Systems and methods for image processing are described. Embodiments of the present disclosure identify a first image depicting a first object; identify a plurality of candidate images depicting a second object; select a second image from the plurality of candidate images depicting the second object based on the second image and a sequence of previous images including the first image using a crop selection network trained to select a next compatible image based on the sequence of previous images; and generate a composite image depicting the first object and the second object based on the first image and the second image.

METHOD AND APPARATUS FOR DETERMINING SLOPE OF ROAD USING SIDE VIEW CAMERA OF VEHICLE

A method and apparatus for determining a slope of a road using a side view camera of a vehicle, the method includes identifying a road image collected from a side view camera, dividing the road image into a plurality of regions, calculating a slope of a road for each of the plurality of regions based on driving lanes comprised in each of the plurality of regions, and determining a slope between the side view camera and the road using the slope of the road calculated for each of the plurality of regions.

METHODS FOR DETECTING PHANTOM PROJECTION ATTACKS AGAINST COMPUTER VISION ALGORITHMS

A system and methods are provided for determining a vehicle action during a phantom projection attack, including processing a received image to identify a traffic object, and creating from the received image multiple processed images that are applied to respective neural network (NN) models. Latent representations of the multiple processed images from each of the NN models are then fed to a combiner model trained to determine whether the latent representations indicate a phantom projection attack, and, responsively to a determination of a phantom projection attack, issuing a phantom projection indicator.

System for the automated, context sensitive, and non-intrusive insertion of consumer-adaptive content in video

Described herein is a method and system for automated, context sensitive and non-intrusive insertion of consumer-adaptive content in video. It assesses ‘context’ in the video that a consumer is viewing through multiple modalities and metadata about the video. The method and system described herein analyzes relevance for a consumer based on multiple factors such as the profile information of the end-user, history of the content, social media and consumer interests and professional or educational background, through patterns from multiple sources. The system also implements local-context through search techniques for localizing sufficiently large, homogenous regions in the image that do not obfuscate protagonists or objects in focus but are viable candidate regions for insertion for the intended content. This makes relevant, curated content available to a user in the most effortless manner without hampering the viewing experience of the main video.