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dibetes-prediction

dibetes-prediction-project

This project include the different kind of use algorithms for the prediction of a person to be diabetic or not using various factors like Insulin level, sugar, skin Thickness, and other factors

did

Learning To Detect In the Dark With Raw Data Image

dlcutils

Various scripts to support deeplabcut...

dmenet

[CVPR 2019] Official TensorFlow Implementation for "Deep Defocus Map Estimation using Domain Adaptation"

doctorbot

DoctorBot is a dialogue-based interactive medical application.

doctorbot-1

A Bot that offers medical assistance. Built with flask

doctorelias

A Medical Expert system made using Experta

drbot

A medical chatbot that can consult doctors and diagnose a disease based on symptoms. Specific attention is given to to out-of-domain question answering.

drqa

A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.

dyslexia

Behavioral Task Code and Stimulus Repository for assessing Orthographic and Phonological processing in children with dyslexia and typical readers.

dyslexia_detection

This project is aimed at developing technology for detecting Dyslexia using just the camera module present in a laptop.

dyslexiaml

Using Machine Learning to detect Dyslexia.

east-detector-for-text-detection-using-opencv-with-word-cropping

Using EAST Text Detector & OpenCV, all the words of an image is detected, cropped and sorted by line from left to right

easyqasystem

my first flask project

eeg_dyslexia_prediction

Predicting dyslexia or dyslexia risk from EEG data

emo-cnn

The emotion plays a key role in many applications like in healthcare domain to gather emotional behaviors. It is very crucial to determine “how it was said” other than “what it was said”, Therefore, in human- machine interaction applications, it is important that emotional states in human speech are fully perceived by ML model well. Our ultimate goal here at FAST lab is to model the stress from emotions. The amount of annotated data is limited and these annotations are highly subjective. Given this common issue in affective computation, the subjectivity lies in the fact that stress perceived by one person may be completely different from the other. Since we are not classifying the data into stress or not stress labels, we must find a way to map these emotions to stress. In short, identify where stress lies in the emotion space. This brings us to many interesting theories in psychology like A&V, PAD and Lovheim cube. What we are trying to acheive here at FAST lab is to see if our deep model: Emo-CNN follows these widely celebrated theories and whether it can model the emotional space described by them.

emotion

:smile: Recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.

emotion-evaluator

:stuck_out_tongue_winking_eye: The Web App, based on NLP, could evaluate speaker's emotion by what they are saying. There are five levels, including Painful, Sad,Normal, Happy, Excited. All of them are expressed by funny emojis. Technologies used in the app includes Python Flask, GCP AppEngine and GCP API(Speech to Text, Natural Language Process ), Bootstrap and etc.

english-dialogpt

A simple implementation of DialoGPT (English)

everypixelmatters

Implementation of ECCV 2020 paper "Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector"

exdark-dataset-to-coco-format

Try to acquire the COCO format with original ExDataset

exdarkyolov3

Changed original ExDark Dataset into yolov3 format

faster-rcnn--object-detection-of-pedestrains-and-cyclists

faster-rcnn-keras

这是一个faster-rcnn的keras实现的库，可以利用voc数据集格式的数据进行训练。

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

fasterrcnn

pytorch-1.1 torchvision-0.3

fasterrcnn-pytorch

FasterRCNN is implemented in VGG, ResNet and FPN base.

flask-api

Browsable web APIs for Flask.

flask-website

The Flask website, built with Flask!