sourolio10 Goto Github PK

advanced-no--contact-doorbell-for-covid-19-issues

azimuth-asctb-ct-ids-analyses

Comparing and flagging the CT-IDs and labels that don't align with ASCTB and vice-versa for next-step action items.

azimuth-asctb-label-comaprison

ccf

HuBMAP CCF Homepage

face-antispoofing-using-mobilenet

Face anti-spoofing using MobileNet

feathernets_face-anti-spoofing-attack-detection-challenge-cvpr2019

Code for 3rd Place Solution in Face Anti-spoofing Attack Detection Challenge @ CVPR2019,model only 0.35M!!! 1.88ms(CPU)

flask-grammar-correction-app

flask-grammar-correction-service

generative-travel-chatbot-journal

Proposal for generative travel chatbot using seq2seq model research paper

hand-gestures

leetcode-practice

makeawish-chatgpt--webapp

Project-Genie for Morgan Stanley Code-to-Give hackathon

models

Models and examples built with TensorFlow

movie-mania

movie-mania-

object-detection-using-yolov3

In recent years, deep learning techniques are achieving state-of-the-art results for object detection, such as on standard benchmark datasets and in computer vision competitions. Notable is the “You Only Look Once,” or YOLO, family of Convolutional Neural Networks that achieve near state-of-the-art results with a single end-to-end model that can perform object detection in real-time. The approach involves a single deep convolutional neural network (originally a version of GoogLeNet, later updated and called DarkNet based on VGG) that splits the input into a grid of cells and each cell directly predicts a bounding box and object classification. The result is a large number of candidate bounding boxes that are consolidated into a final prediction by a post-processing step. There are three main variations of the approach, at the time of writing; they are YOLOv1, YOLOv2, and YOLOv3. The first version proposed the general architecture, whereas the second version refined the design and made use of predefined anchor boxes to improve bounding box proposal, and version three further refined the model architecture and training process.

ontology-mapper

Tool for mapping (uncontrolled) terms to ontology terms

pos-tagging-and-ocr

react-practice

realtime-face-antispoofing-using-mobilenet

sign-language-recognition-with-rnn-and-mediapipe

souradeep-portfolio.github.io

sourolio10.github.io

stock-market-prediction

stockhive

Time-series forecasts of stock data

tourdemonde

viet-nam-sign-language-recognition-using-hand-mediapipe-framework-and-lstm-model

weather-forecast-schedule-github-actions

word-wise

Word Wise Webapp

word-wise-frontend