Mannansinghvi

Mannansinghvi's Stars

• vijaysumaravi/USSD-depression

  A Privacy-preserving Unsupervised Speaker Disentanglement Method for Depression Detection from Speech

  Language:Python1

• belal981/depression-detection

  Depression-Detection represents a machine learning algorithm to classify audio using acoustic features in human speech, thus detecting depressive episodes and patterns through sessions with user. The method is tailored to lower the entry barrier when finding help mental disorder and diagram-support for medical professionals ours.

  Language:Jupyter Notebook131

• mltlachac/DepreST-CAT

  Dataset consisting of call and text logs labeled with mental illness screening surveys scores

  Language:Jupyter Notebook4

• speechandlanguageprocessing/ICASSP2022-Depression

  Automatic Depression Detection: a GRU/ BiLSTM-based Model and An Emotional Audio-Textual Corpus

  Language:Python11130

• G0rav/Human_Activity_Recognition

  The MHEALTH (Mobile Health) dataset is devised to benchmark techniques dealing with human behavior analysis based on multimodal body sensing.

  Language:Jupyter Notebook173

• dimitriliaki/applicationsAi

  this project contains an nlp algorithm for detection of depression in Daic-Woz dataset

  Language:Jupyter Notebook4

• divertingPan/STA-DRN

  code for paper 'Spatial-Temporal Attention Network for Depression Recognition from Facial Videos'

  Language:Python162

• cosmaadrian/multimodal-depression-from-video

  Official source code for the paper: "Reading Between the Frames Multi-Modal Non-Verbal Depression Detection in Videos"

  Language:Python272

• cosmaadrian/time-enriched-multimodal-depression-detection

  Official source code for the paper: "It’s Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers"

  Language:Python402

• vanditagoyal1997/depression-analysis

  To examine the feasibility of and aim to use different behavioral indicators for depression, consisting of, but not limited to, visual and audio features to design an effective testing model which can be made more accessible than traditional testing methods.

  Language:Jupyter Notebook62

• gangeshbaskerr/Early-Depression-Detection

  I developed a depression detection system through multi-model data integrating word context, audio, and video to predict if a patient exhibits symptoms of depression (binary yes/no). The deep learning architecture involves feedforward highway layers for audio and video, dimensionality reduction using dense layers, concatenation, (Bi)LSTM, and a fin

  Language:Jupyter Notebook3

• Harshitamaurya/Depression-Detection-using-Text-and-Audio

  Language:Jupyter Notebook2

• serenera/Serenera

  Monitor Chrome Browsing to detect levels of Depression

  Language:Python178

• yijiazh/DFER_Summer2019

  Language:Python31

• Fuzzy-sh/Risk-Assessment-and-Predicting-Homelessness-and-Police-Interaction-in-Calgary-Through-Administrative

  Machine Learning Risk Estimation and Prediction of Homelessness and Police interaction for individuals living in Calgary diagnosed with mental illness using Administrative Data

  Language:Jupyter Notebook4

• adityapotdar23/DJSCE-24-Placements-Interview-Experience

  13

• kyang01/startup-analysis

  Language:Jupyter Notebook148

• RamkishanPanthena/Startup-Success-Prediction

  An interactive machine learning and data visualization project

  Language:Jupyter Notebook3923

• londonappbrewery/Clima-Flutter

  Starter code for the Clima Project from the Complete Flutter Development Bootcamp

  Language:Dart152741

• tharwatsamy/Flutter-Beginners-Projects

  Language:Dart606126

• har200105/striverSDESheet

  A Complete Solution of the well known 'Striver SDE Sheet ' in C++.

  Language:C++8424

• jakansha2001/mental_health_app_ui

  Language:Dart3410

• JayTWWM/AI-Therapist

  A Flask and Deep Learning Project that recognizes the emotion/mood of the user via either a photo or voice or text given as input by the user. It also contains a chatbot!

  Language:Jupyter Notebook71

• pik1989/EDAforHealthcare

  Language:Jupyter Notebook1214

• Manu-Gr/Multi-Linear-Regression---Assignment---50-Startups

  Multi Linear Regression - Assignment - 50 Startups

  Language:Jupyter Notebook11

• etorqweku/Career_Accelerator_LP1-Data_Analysis

  Language:Jupyter Notebook1

• londonappbrewery/Flutter-Course-Resources

  Learn to Code While Building Apps - The Complete Flutter Development Bootcamp

  10.1k3k

• londonappbrewery/quizzler-flutter-challenge-starting

  Starter code for the Quizzler Challenge from the Complete Flutter Development Bootcamp

  Language:Dart49155

• ioangatop/DataMining

  Data Mining techniques on predicting mood using time-series analysis in mental health and predicting the click behaviour of users in a hotel ranking system.

  Language:Jupyter Notebook3

• chiayunchiang/Mental-Health-Survey-Analysis-and-Prediction-Model

  Language:Jupyter Notebook1