Pinned Repositories
2019_jinnan2_x-ray-detection
2019_jinnan2_x-ray-detection
Agriculture_KnowledgeGraph
农业知识图谱(AgriKG):农业领域的信息检索,命名实体识别,关系抽取,智能问答,辅助决策
algorithm
「面试算法练级攻略」 - 「LeetCode题解」 - 「剑指offer题解」
anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
APTOS2019
43th place (top2%) Solution for Kaggle APTOS 2019 Blindness Detection
BELLE
BELLE: Be Everyone's Large Language model Engine(开源中文对话大模型)
Camelyon17
Camelyon17 (Breast Tumor Classification)
optical-flow-for-weather-forecast
Weather Radar Echo Forecast using opencv+GPU,it can real-time operation and half an hour is reliable.
WeatherRadarEchoClassfication
WeatherRadarScanSimulation
lelegogo26's Repositories
lelegogo26/data_science_bowl_2018
My 5th place (out of 816 teams) solution to The 2018 Data Science Bowl organized by Booz Allen Hamilton
lelegogo26/algorithm
「面试算法练级攻略」 - 「LeetCode题解」 - 「剑指offer题解」
lelegogo26/2019_jinnan2_x-ray-detection
2019_jinnan2_x-ray-detection
lelegogo26/pytorch-nested-unet
PyTorch implementation of UNet++ (Nested U-Net).
lelegogo26/optical-flow-for-weather-forecast
Weather Radar Echo Forecast using opencv+GPU,it can real-time operation and half an hour is reliable.
lelegogo26/unet-tensorflow-keras
A concise code for training and evaluating Unet using tensorflow+keras
lelegogo26/LovaszSoftmax
Code for the Lovász-Softmax loss (CVPR 2018)
lelegogo26/Pneumonia-Diagnosis-using-XRays-96-percent-Recall
BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.
lelegogo26/the-gan-zoo
A list of all named GANs!
lelegogo26/SAGAN
Sharpness-aware Low Dose CT Denoising Using Conditional Generative Adversarial Network
lelegogo26/pcam
The PatchCamelyon (PCam) deep learning classification benchmark.
lelegogo26/TensorExpand
集成包
lelegogo26/TernausNet
UNet model with VGG11 encoder pre-trained on Kaggle Carvana dataset
lelegogo26/Diabetic_Reinopathy_Dectection
糖网眼底图像分类_pytorch
lelegogo26/kaggle-dstl
Kaggle DSTL Satellite Imagery Feature Detection
lelegogo26/Camelyon17
Camelyon17 (Breast Tumor Classification)
lelegogo26/DSB2017
The solution of team 'grt123' in DSB2017
lelegogo26/tensorflow-model-zoo.torch
InceptionV3, InceptionV4, Inception-Resnet pretrained models for Torch7 and PyTorch
lelegogo26/dream2016_dm
My entry to the DREAM2016 digital mammography challenge for breast cancer diagnosis
lelegogo26/intel-cancer
Kaggle Intel & MobileODT Cervical Cancer Screening (4th place solution)
lelegogo26/intel-cervical-cancer
Team GuYuShiJie~'s 15th (top 2%) solution of cervix type classification in Kaggle 2017 competition, using PyTorch.
lelegogo26/cnn4brca
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis
lelegogo26/Kaggle-MobileODT
Code for Intel & MobileODT Cervical Cancer Screening competition on Kaggle https://www.kaggle.com/c/intel-mobileodt-cervical-cancer-screening
lelegogo26/Dstl-Satellite-Imagery-Feature-Detection
Place 18 solution for the Dstl feature detection kaggle challenge https://www.kaggle.com/c/dstl-satellite-imagery-feature-detection
lelegogo26/kaggle-breast-cancer-prediction
Different approaches as (ANN,DecisionTree,Bayes and KNeighbors) to solve and predict with the best accuracy malignous cancers