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depression-detection-1

depression-detection-2

Depression detection using multi-modal fusion framework composed of deep convolutional neural network (DCNN) and deep neural network (DNN) models.

depression-detection-through-multi-modal-data

Conventionally depression detection was done through extensive clinical interviews, wherein the subject’s re- sponses are studied by the psychologist to determine his/her mental state. In our model, we try to imbibe this approach by fusing the 3 modalities i.e. word context, audio, and video and predict an output regarding the mental health of the patient. The output is divided into a binary yes/no denoting whether the patient has symptoms of depression. We’ve built a deep learning model that fuses these 3 modalities, assigning them appropriate weights, and thus gives an output.

depression-detection_reddit_comments

Depression Detection github.io

depression-identification

Depression detection and severity estimation

depression-sentiment-prediction

Depression Sentiment Prediction Project

depression_detection

Affective Computing project

depression_estimation_from_individual_modalities

depression_level_regression_from_individual_modalities

depressiondetection

Multi-modal depression detection

depressiondetectionnlp

Final Group ProjeDetecting Human Emotions Using Natural Language Processing UCB Data Analytics

depressionresearch

2018/2019 HIT - Depression Research

depressionvsbipolar

detecting-deception-in-political-debates

detectron-doc

My tutorials for object detection for Detectron2, Mediapipe, VideoPose3d, AlphaPose, Metrabs

diagnose-covid-19-from-respiratory-sound

diagnose-report

Simple android application that help patients to manage their medical reports.

differentiating_depression_and_suicide

A text analytics project centered on understanding the r/Depression and r/SuicideWatch subreddits

dilatedrnn

Tensorflow implementation for DilatedRNN

dimensional-ser

Repository for my paper: Dimensional Speech Emotion Recognition Using Acoustic Features and Word Embeddings using Multitask Learning

dimensional_ser_rnn

Repository for coding Dimensional speech emotion recognition from acoustic and text

discerning-suicidal-ideation-from-the-language-of-depression

Natural Language Processing (NLP) applied to over 200,000 subreddit submissions to correctly identify subset containing suicidality with applications for advancing clinical suicide prevention research.

discsense

Automated Semantic Analysis of Discourse Markers

displacenet

DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance Level - CVPR '19 Workshop on Computer Vision for Global Challenges

dl-4-tsc

Deep Learning for Time Series Classification

dl-colab-notebooks

Try out deep learning models online on Google Colab

dl-for-har-comparison

Comparison of frequently used deep learning architectures (LSTM, biLSTM, GRU and CNN) on ten Human Activity Recognition datasets.

dl-massive-mimo

DL tackling Massive-MIMO problems

dl-text

Text pre-processing modules for deep learning (Keras, tensorflow).

dlatk

End to end human text analysis package, specifically suited for social media and social scientific applications. It is written in Python 3 and developed by the World Well-Being Project at the University of Pennsylvania.