rajtapase Goto Github PK

-real-time-vehicle-classification-and-localization-using-edge-computing-

The project aims to develop a traffic monitoring system using convolution neural network. We had modified existing tiny YOLO model for Indian vehicle such as auto rickshaw, bicycle, motorbikes etc. To do this, first we developed a data set of these vehicles then we retrained the existing tiny YOLO model. Moreover, with raspberry Pi we have developed a prototype for edge device which can count incoming and outgoing traffic from a particular point. There are various applications of such devices for example, it can be used as traffic monitoring system, surveillance, traffic load prediction. This is a fully functional independent device. All the decision has been done locally, this make this device highly useful for IoTs.

angular_mini-project

angular_task_1

angular_task_2

battery-saver-android-app

Mcan mini project of battery saver which disables wifi, bluetooth and reduces screen brightness when battery is below 65%

bluetooth_messenger

this application bluetooth to send messages between devices

bridgefy-android-samples

The repository for the official samples for the Bridgefy SDK for Android

chatbot-using-recurrent-neural-networks

A conversational agent or a chatbot is piece of software which can communicate with human users with the help of natural language processing (NLP). Modelling conversation is a very crucial task in natural language processing and artificial intelligence (AI). Since the discovery of artificial intelligence, creating a good chatbot is one of the field’s hardest and complex challenges. Chatbots can be used for various tasks such as make phone calls, provide reminders etc; in general they have to understand users’ utterances and provide relevant responses for the problem in hand. Previously, methods which were used for constructing chatbot architectures relied on hand-written rules, templates or simple statistical methods. Rising and innovating field of deep learning have replaced previous models with trainable neural network models. The recurrent encoder-decoder model is the dominating model in the field modelling conversations. Multiple variations and features have been presented that have changed the quality of the conversation that chatbots are capable of. In our project, we have surveyed recent literatures published, examining various publications related to chatbots. We started with taking Cornell movie dialogue corpus as our dataset then after training our model with it and fine tuning it with various parameters, non-satisfactory results lead us to take another dataset and we trained and tested our final model on modified Gunthercox dataset which gave us satisfactory results for an open domain chatbot or general domain chatbot.

coursera-specializations

Specialization courses in Coursera

css-ia-tool

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

gate-material

ibm-ai-engineering-specialization

lane-detection-using-deep-learning

Autonomous self-driving is in the trend for implementing it in our real life to remove all the hassles and accidents. Modern-day transport has come a long way but still far away from perfection and all-around safety. Lane Detection is a concept of demarcating lanes on the roads while the vehicle is moving. It has the capability of changing the vehicular movements on road, making them more organized and safe. This leap could provide for driver carelessness and avoid a lot of mishaps on the roads. Ride-hailing services like Uber and Ola can use them to monitor drivers and rate them based on driving skills. We have designed and trained a deep Convolutional Network model from scratch for lane detection since a CNN based model is known to work best for image datasets. We have used BDD100k dataset for training and testing for our model. We have used various metrics values for hyper-parameters tuning and took the ones which gave the best result. The training is done on Supercomputer NVIDIA-DGX V100. Idea By: Aditya Sharma, Microsoft

online-cse-nitk-website-and-management-software

openssl-resources

OpenSSL - Cryptographic tool

payroll-manangement-system

Payroll Management System using NodeJs, Express, EJS , Mongoose, Pdfmake.

qualys-intranet-scanner

raven

RAVEN is a flexible and multi-purpose probabilistic risk analysis, uncertainty quantification, parameter optimization and data knowledge-discovering framework.

spcc-2019

all SPCC programs for VI sem

vaastu

AIT project

wifi_analyzer2

3rd year MCAN experiment