manyasrinivas2021

AI-BASED-FACIAL-EMOTION-DETECTION-USING-DEEP-LEARNING

“AI Based Facial Emotion Detection”, developed using many machine learning algorithms including convolution neural networks (CNN) for a facial expression recognition task. The goal is to classify each facial image into one of the seven facial emotion categories considered in this study.Trained CNN models with different depth using gray-scale images from the Kaggle website.CNN models are developed in Pytorch and exploited Graphics Processing Unit (GPU) computation in order to expedite the training process. In addition to the networks performing based on raw pixel data,Hybrid feature strategy is employed by which trained a novel CNN model with the combination of raw pixel data and Histogram of Oriented Gradients (HOG) features. To reduce the over fitting of the models,different techniques are utilized including dropout and batch normalization in addition to L2 regularization. Cross validation is applied to determine the optimal hyper-parameters and evaluated the performance of the developed models by looking at their training histories. Visualization of different layers of a network is presented to show what features of a face can be learned by CNN models. Based on the emotion the program recommends the music for the user to up flit the mood.

ARTIFICIAL-INTELLIGENCE-HEALTHCARE-CHATBOT-SYSTEM-USING-PYTHON

Through chatbots one can communicate with text or voice interface and get reply through Artificial intelligence. Typically, a chat bot will communicate with a real person. Chat bots are used in applications such as ecommerce customer service, call centres and Internet gaming. Chatbots are programs built to automatically engage with received messages. Chatbots can be programmed to respond the same way each time, to respond differently to messages containing certain keywords and even to use machine learning to adapt their responses to fit the situation. A developing number of hospitals, nursing homes, and even private centres, presently utilize online Chatbots for human services on their sites. These bots connect with potential patients visiting the site, helping them discover specialists, booking their appointments, and getting them access to the correct treatment. In any case, the utilization of Artificial intelligence in an industry where individuals’ lives could be in question, still starts misgivings in individuals. It brings up issues about whether the task mentioned above ought to be assigned to human staff. This healthcare chatbot system will help hospitals to provide healthcare support online 24 x 7, it answers deep as well as general questions. It also helps to generate leads and automatically delivers the information of leads to sales. By asking the questions in series it helps patients by guiding what exactly he/she is looking for.

d2b

datatobi

HEATHCARE-CHATBOT-SYSTEM-USING-PYTHON

Identification-of-phonenumber-s-country-service-provider

To identify the phone numbers ,country and service provider

image-display

Displaying the image using python code

OBJECT-DETECTION-USING-OPENCV

identifies the objects

pdftotext

Simple PDF text extraction

speech_to_text

converts speech to text

manyasrinivas2021/AI-BASED-FACIAL-EMOTION-DETECTION-USING-DEEP-LEARNING

“AI Based Facial Emotion Detection”, developed using many machine learning algorithms including convolution neural networks (CNN) for a facial expression recognition task. The goal is to classify each facial image into one of the seven facial emotion categories considered in this study.Trained CNN models with different depth using gray-scale images from the Kaggle website.CNN models are developed in Pytorch and exploited Graphics Processing Unit (GPU) computation in order to expedite the training process. In addition to the networks performing based on raw pixel data,Hybrid feature strategy is employed by which trained a novel CNN model with the combination of raw pixel data and Histogram of Oriented Gradients (HOG) features. To reduce the over fitting of the models,different techniques are utilized including dropout and batch normalization in addition to L2 regularization. Cross validation is applied to determine the optimal hyper-parameters and evaluated the performance of the developed models by looking at their training histories. Visualization of different layers of a network is presented to show what features of a face can be learned by CNN models. Based on the emotion the program recommends the music for the user to up flit the mood.

manyasrinivas2021/ARTIFICIAL-INTELLIGENCE-HEALTHCARE-CHATBOT-SYSTEM-USING-PYTHON

Through chatbots one can communicate with text or voice interface and get reply through Artificial intelligence. Typically, a chat bot will communicate with a real person. Chat bots are used in applications such as ecommerce customer service, call centres and Internet gaming. Chatbots are programs built to automatically engage with received messages. Chatbots can be programmed to respond the same way each time, to respond differently to messages containing certain keywords and even to use machine learning to adapt their responses to fit the situation. A developing number of hospitals, nursing homes, and even private centres, presently utilize online Chatbots for human services on their sites. These bots connect with potential patients visiting the site, helping them discover specialists, booking their appointments, and getting them access to the correct treatment. In any case, the utilization of Artificial intelligence in an industry where individuals’ lives could be in question, still starts misgivings in individuals. It brings up issues about whether the task mentioned above ought to be assigned to human staff. This healthcare chatbot system will help hospitals to provide healthcare support online 24 x 7, it answers deep as well as general questions. It also helps to generate leads and automatically delivers the information of leads to sales. By asking the questions in series it helps patients by guiding what exactly he/she is looking for.

manyasrinivas2021/d2b

manyasrinivas2021/datatobi

manyasrinivas2021/HEATHCARE-CHATBOT-SYSTEM-USING-PYTHON

manyasrinivas2021/Identification-of-phonenumber-s-country-service-provider

To identify the phone numbers ,country and service provider

manyasrinivas2021/image-display

Displaying the image using python code

manyasrinivas2021/OBJECT-DETECTION-USING-OPENCV

identifies the objects

manyasrinivas2021/pdftotext

Simple PDF text extraction

manyasrinivas2021/speech_to_text

converts speech to text

manyasrinivas2021/test-repo