Search Results for "3d model"

...In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support, distributed graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour).

This is a work in progress split-flap display. Each module can flip between 40 unique characters: letters, numbers, and a few symbols. Multiple modules fit perfectly alongside each other to build bigger displays. The primary design goal was to make something that's possible to fabricate at home in small or single quantities and can be customized and built by an intermediate hobbyist at a reasonable price. This meant using widely available materials and avoiding any tooling with a high...

LaMa is a C++11 software library for robotic localization and mapping developed at the Intelligent Robotics and Systems (IRIS) Laboratory at the University of Aveiro - Portugal. It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM). The main feature is efficiency. Low computational effort and low memory usage whenever possible. The minimum viable computer to run our localization and SLAM solutions is a Raspberry Pi 3 Model B+. ...

...Built around an ESP32 PICO-D4 microcontroller, a 1.3″ 240×240 ST7789 display and MPU6050 inertial sensor, the device allows you to build a “floating hologram” style display module with additional networked visual features like weather display or follower counts. The hardware design includes versions of the PCB (Naive version, Ironman version) and 3D model files for the enclosure (3D printed or CNC metal). The software leverages LVGL (a GUI library for microcontrollers) and supports surface touch or IMU-based input. Because it connects via WiFi/Bluetooth, it can fetch live data and display dynamic content, bridging embedded display, network, and interactive gadget design.

TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the...

...This project aims to make the expanse of human knowledge beautifully presentable and the exabytes of data navigable by an average user via the power of a Unified Data Model and 3d visualization layer for the Web. It will invert the top 3 layers of the OSI network model to make a 3-dimensional presentation layer with a peer-to-peer session layer for the Internet. For the curious, there is a simple demo that provides a small sense of the possibilities. Requires: VPython available here or see http://vpython.org.

The first 3D game engine built in C# for .NET, predecessor to the Visual3D Game Engine (https://www.poweraccess.net/visual3d-game-engine), an All-in-One Game Development Tool for Next-Gen 3D Games, MMOs, Simulations and Virtual Worlds powered by Microsoft XNA.