PapaNorfans

PapaNorfans

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Cellular-Automata-Traffic-Simulation

Research on The Impact of Road Traffic Around on Opening Residential Community Based on Cellular Automaton

Language:MATLABStargazers:13Issues:0Issues:0

breast_cancer_diagnosis

Development of deep learning tool to classify breast cancer images from CBIS-DDSM, INBreast and MIAS databases.

Language:PythonLicense:MITStargazers:24Issues:0Issues:0

Breast-cancer-diagnosis-using-Machine-Learning

Machine learning is widely used in bioinformatics and particularly in breast cancer diagnosis. In this project, certain classification methods such as K-nearest neighbors (K-NN) and Support Vector Machine (SVM) which is a supervised learning method to detect breast cancer are used.

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Cancer_diagnosis_classifier

All files related to the development of a personal project in Java to diagnose breast cancer out of tumor images using pattern recognition techniques (Machine Learning).

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AI_Crime_Analytics

Generate a crime risk map and find an optimal path between any two coordinates on the map using A* heuristic algorithm. The optimal path generated will avoid high-risk areas on the map.

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AddisMap

A Django App that finds the path between two points (selected by the user) on a real world map, using different path finding algorithms (Dijkstra, A-Star, BFS, Greedy-First...) On top of that, the app creates a visualizer for each algorithm to get a better grasp of how the algorithm finds the shortest path. A comparison to the shortest path found by Google Maps is also generated to judge the accuracy of the shortest path found by this app.

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dijkstra-py-mini-thesis

Finding shortest path on map

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route-planner

Route Planner. Find the shortest path on the map

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Optimal-Path-Planning

Implementation of the A* search alogirthm to find an optimal path on a generated map.

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year-round-orienting

In this lab, you will be generating optimal paths for orienteering during different seasons. In the sport (or "activity", depending on your level of fitness/competitiveness) of orienteering, you are given a map with terrain information, elevation contours, and a set or sequence of locations to visit ("controls"). There is a combination of athletic skills and planning skills required to succeed - a smarter competitor who can figure out the best way to get from point to point may beat out a more athletic competitor who makes poor choices! In this lab, you are given computer-friendly inputs so that you can use an algorithm to determine the best path for you to take depending on your ability.

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multi-step-Q-learning-and-SARSA

Finding the optimum path on a map using the SARSA and Q-learning algorithms

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-AI-based-navigation-system

Artificial intelligence in GPS navigation systems. Abstract: GPS navigation systems use stored map information for determining optimal route selection based on a shortest path algorithm. ... All of the required information is derived from recording GPS location, date and time.

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neo4j_autonomous_path_planner_project

An optimum algorithm for autonomous mobile robots (AMR) navigation based on graph structure of the input_map (pgm or png) using cloud service-AWS or Neo4j services.

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Evasive-Path-Planning

Details an assortment of algorithms to find the path which optimally evades an observers on a grid-based map which can be customized

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smart-video-workshop

Learn about the workflow using Intel® Distribution of OpenVINO™ toolkit to accelerate vision, automatic speech recognition, natural language processing, recommendation systems and many other applications.

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DeepNaturalLanguageProcessing

DeepLearning in Natural Language Processing including Language Model, Part of Sentence, Chinese Segmentation,Named Entity Recognition and so on.

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FacebookBot

A Facebook Messenger Bot that supports Voice Recognition, Natural Language Processing and features such as: search nearby restaurants, search trending news, transcribe and save memos to the cloud.

Language:JavaScriptLicense:MITStargazers:1390Issues:0Issues:0

Intelligent_CropPrediction_System

An Intelligent Crop Recommendation system using Machine Learning that predicts crop suitability by factoring all relevant data such as temperature, rainfall, location, and soil condition. This system is primarily concerned with performing AgroConsultant's principal role, which is to provide crop recommendations to farmers.

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:9Issues:0Issues:0