CMTeamF

CMTeamF's Stars

• guillaumebour/flexible-job-shop

  Python implementation of a genetic algorithm for FJSP.

  Language:Python9039

• GuilhermeBaldo/GA-FJSP

  Genetic algorithm for the flexible job-shop scheduling problem

  Language:Python243

• JoshuaShi-19/FJSP

  毕业论文-遗传算法-柔性生产调度

  Language:MATLAB357

• NJU-Nonames/Logistics-System

  软工大作业 物流系统

  Language:Java1211

• yunjianfei/Logistics-Management-System

  大学时期的小作品--物流管理系统

  Language:Java7238

• anselleeyy/logistics-back

  物流后端项目，采用 Springboot 2.0 + Layui 2.3

  Language:Java547259

• GuiyinLi/ELF-Analysis

  实现readelf指令的-h, -S, -l和-d

  Language:C1

• GrandChris/elf_analysis

  Reads an .elf file, disassembles the '.text' section and decodes the '.debug_line' section.

  Language:C++4

• andreadaru/ELF_AnalyserAndPlot

  This program plots on a graph the electronic variations around the atoms along an IRC calculation of a chemical reaction. From the out files generated by ELF calculation, that contain information about geometry, basin and values of them.

  Language:Shell1

• Guofx98/ELF-analysis

  解析Linux中的ELF文件（32位或64位）

  Language:C43

• gigo2191/ELFDynamicAnalysis

  ELF 포맷 파일 동적 분석기. 프로토 타입

  Language:C++1

• bigGreenPeople/ElfAnalysis

  ELF文件格式解析

  Language:C4

• AshishRanaX/elf_analysis

  Perform Static and dynamic analysis on 32 bit ELF binary, and automate the process of stack based overflow exploitation.

  Language:Python467

• YaoHaozhe/Computer-vision-based-on-deep-learning-garbage-classification

  2

  Language:Python7336

• Lanhl2016/LL1grammar

  LL（1）语法分析器的C++代码实现，实现过程是手动输入分析器的预测分析表

  Language:C++43

• mayuri0192/Image-classification

  Image Classification using SIFT, Bag of words, k means clustering and SVM Classification

  Language:Python7928

• opencv/opencv

  Open Source Computer Vision Library

  Language:C++78.1k55.7k

• francismontalbo/fused-densenet-tiny

  A novel approach in training a DenseNet model for diagnosing COVID-19 Chest X-Rays.

  Language:Jupyter Notebook295

• iamsouravbanerjee/COVID-19-Detection-from-X-Ray-Images

  Analyzing various chest X-Rays and making an image detector which will help us detect COVID-19, using Haar Cascade. This is a Multiclass Classification problem.

  Language:Jupyter Notebook1

• maruthi1986/Lung-Cancer-Classification

  The primary goal of developing a smart city is to enhance the quality of lives of its citizens by providing infrastructure and offering smart healthcare. Smart Healthcare plays a significant role in achieving this objective of developing smart cities. Here, in this proposal our objective is to develop a smart health care system which uses artificial intelligence for the development of a decision support system in the medical field for the detection and segmentation of lung cancer. The proposed system is consisting of two phases, First phase will be consisting of various stages like Pre-processing, feature extraction, feature selection, classification and finally segmentation of the tumor. Input CT image is sent through the pre-processing phase where noise removal will be taken care and then texture features are extracted from the pre-processed image, and in the next stage features will be selected by making use of Crow Search Optimization Algorithm, later Artificial Neural Network is used for the classification of the normal lung images from abnormal images. Finally, abnormal images will be processed through the Fuzzy K-Means algorithm for segmenting the tumors separately. In the second phase, SVM classifier is used for the reduction of false positives. This methodology delivers a 96% of accuracy, 100% specificity and sensitivity of 99%. The accuracy of the decision taken by the Smart Health Care System exceed when compared to the accuracy of the decision taken by the doctors.

  Language:MATLAB103

• ng0227/Image-Processing-Lung-disease-detection-using-feature-selection-and-machine-learning

  A Computer Aided Diagnosis (CAD) system to diagnose lung diseases: COPD and Pulmonary Fibrosis using chest CT images

  Language:Python267

• eivindhammers/hog-covid19

  Head of Government and Covid-19 outcomes

  Language:R1

• ardahuseyinoglu/xray-image-classification-with-knn

  Implementation of a K-NN and weighted K-NN algorithm from scratch to detect covid-19 disease from images, using HOG and deep (resnet-50) features.

  Language:Jupyter Notebook3

• niyishakapatrick/Using-Illumination-and-LBP-on-COVID-CT-Dataset-COVID-19-

  Using Illumination, LBP and Machine Learning techniques on COVID-CT-Dataset( COVID-19):

  1

• Dophy6/LBP-COVID-19-Recognition

  Local Binary Pattern: COVID-19 Recognition

  Language:Python11

• ayciceksamet/Covid-CT-Image-Classification-Using-HOG-Feature

  Classification performed Using HOG Feature - Python - Google Collab Environment

  Language:Jupyter Notebook1

• jasongong11/covid_x_ray_classification_cnn_sift_svm

  This final project is a classification model for Stat 208, Davis 2021 spring class. Instructor: James Sharpna.

  Language:Jupyter Notebook1