APPARATUS AND METHOD OF GUIDED NEURAL NETWORK MODEL FOR IMAGE PROCESSING

A new system helps change the style of one image using another image's style. It starts by creating special maps from both the original image and the style image. These maps provide important information about how to combine the two images. Then, a network uses this information to blend the images together. Finally, the system produces a new image that looks like the first one but with the style of the second one.

CROSS REALITY SYSTEM

A cross reality system creates an engaging experience by keeping track of important spatial details about the real world. This information helps devices understand their location and allows virtual objects to be placed accurately in the physical space. Users can share both virtual and real experiences while using the system, making it easier to interact with their surroundings. The system can also use stored maps of the environment, so users don’t need to map everything out each time they want to use it. It works by capturing images of a 3D area, identifying key features, and creating coordinate frames that help maintain a consistent understanding of the space.

METHOD AND ARRANGEMENTS FOR GRAPHICALLY VISUALIZING DATA TRANSFER IN A 3D VIRTUAL ENVIRONMENT

A method allows users to see data transfers happening in a 3D virtual environment using their device. Users experience this environment from a first-person perspective, which means they see it as if they are actually there. When data is sent between two other devices, the user can see a visual representation of this transfer in the virtual space. This visualization shows a flow of data between different virtual locations linked to the devices involved. By doing this, users can better understand how data moves in the 3D environment they are exploring.

ROAD EXPERIENCE MANAGEMENT (REM) MAP FEATURES DELIVERED VIA AUGMENTED REALITY (AR)

Augmented reality (AR) can be used to show different types of information to users while they are on the road. This information can come from various sources, like objects detected by a vehicle or content created by other users. It can also include data collected from crowdsourced maps. The AR displays will present this information in a way that fits the user's view, making it look like the digital details are part of the real world. This helps drivers understand their surroundings better and enhances their overall driving experience.

Systems And Methods For Autonomous Validation of Crowd Sourced and Open Sourced Information

A system has been developed to check the accuracy of information gathered from various sources, like social media and sensors. It collects data about events from multiple devices and analyzes this information to see how trustworthy it is. By comparing different sources of information, the system can verify if the details about an event are correct. If the information is confirmed as reliable, it can automatically send alerts or guidance to relevant people. This technology aims to improve safety and response times by ensuring that only credible information is shared during emergencies.

WILDFIRE DEFENSE SPRAYING PROCESS FOR AUTOMATICALLY SPRAYING ENVIRONMENTALLY-CLEAN WATER-BASED LIQUID FIRE INHIBITOR OVER COMBUSTIBLE PROPERTY SURFACES TO FORM THIN FIRE-INHIBITING POTASSIUM SALT CRYSTALLINE COATINGS THEREON BEFORE PRESENCE OF WILDFIRE

A new process helps protect properties from wildfires by spraying a safe, water-based liquid that prevents fires. This liquid contains a mix of potassium salts and stays stable without forming solids, making it ready for immediate use. When a wildfire is detected, an automated system triggers a pump to spray the liquid over the property. After spraying, the water in the liquid evaporates, leaving behind a thin layer of potassium salt crystals on surfaces. These crystals help stop fires from starting and spreading when embers from wildfires are present.

SEMICONDUCTOR DEVICE, FINFET DEVICE AND METHODS OF FORMING THE SAME

A semiconductor device has a base layer called a substrate. On top of this layer, there is a gate structure that helps control the flow of electricity. Next to the gate, there are areas known as source/drain regions that allow electrical connections. A special contact connects to these source/drain regions and wraps around them for better performance. This design helps improve the efficiency and functionality of the device.

SEMICONDUCTOR DEVICE AND MANUFACTURING METHOD THEREOF

A semiconductor device has a base made of a special material called a semiconductor, which is divided into two areas. Each area contains thin structures known as semiconductor fins, which have different shapes; one type is uniform in width, while the other tapers in the middle. Insulators are placed on the base to separate these fins. Above some parts of the fins, there are gate stacks that help control electrical signals. Additionally, there are source and drain regions that connect to other parts of the fins to complete the device's function.

NON-VOLATILE MEMORY CELL STRUCTURES AND METHODS OF MANUFACTURING THEREOF

A new type of memory device has been created with different regions that help store information. It has a main area in the middle, surrounded by other areas that work together to manage data. Floating gates are placed above these regions, allowing them to connect and store data effectively. There are special sections for writing and reading data, each with their own source and drain regions to help with the process. This design aims to improve how memory devices function and retain information.

COMPUTE OPTIMIZATION MECHANISM FOR DEEP NEURAL NETWORKS

A new system helps improve how computers perform calculations for deep neural networks, which are used in tasks like image and speech recognition. It includes a graphics processing unit (GPU) that has several multiprocessors, each with its own storage for different types of data. The GPU has two groups of processing cores: one group works with one memory channel, while the other group uses a different memory channel. This setup allows for more efficient processing by distributing tasks between the two types of cores. Overall, it aims to make deep learning computations faster and more effective.