Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*

Last update: Mar 28, 2022

Overview

Optimized-Path-Analysis-for-an-Underground-Cave-System-3D-Maze-

Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*. The algorithm was extremely optimal running in ~15s to ~30s for search spaces as big as 10000000 nodes where a set of 18 actions could be performed at each node in the 3D Maze.

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GitHub Repository

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Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*

Related tags

Overview

Optimized-Path-Analysis-for-an-Underground-Cave-System-3D-Maze-

Owner

SEJE Pytorch implementation

Code release for DS-NeRF (Depth-supervised Neural Radiance Fields)

An example of Scatterbrain implementation (combining local attention and Performer)

HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives

Detection of drones using their thermal signatures from thermal camera through YOLO-V3 based CNN with modifications to encapsulate drone motion

MusicYOLO framework uses the object detection model, YOLOx, to locate notes in the spectrogram.

Deep universal probabilistic programming with Python and PyTorch

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Data and extra materials for the food safety publications classifier

Exploring Versatile Prior for Human Motion via Motion Frequency Guidance (3DV2021)

Code for "Neural 3D Scene Reconstruction with the Manhattan-world Assumption" CVPR 2022 Oral

Set of models for classifcation of 3D volumes

This is the code repository implementing the paper "TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction".

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