Live Updates: COVID-19 Cases
  • World 19,606,083
    World
    Confirmed: 19,606,083
    Active: 6,293,248
    Recovered: 12,587,767
    Death: 725,068
  • USA 5,100,909
    USA
    Confirmed: 5,100,909
    Active: 2,318,522
    Recovered: 2,618,191
    Death: 164,196
  • Brazil 2,967,064
    Brazil
    Confirmed: 2,967,064
    Active: 798,968
    Recovered: 2,068,394
    Death: 99,702
  • India 2,114,140
    India
    Confirmed: 2,114,140
    Active: 628,136
    Recovered: 1,443,183
    Death: 42,821
  • Russia 882,347
    Russia
    Confirmed: 882,347
    Active: 177,286
    Recovered: 690,207
    Death: 14,854
  • South Africa 545,476
    South Africa
    Confirmed: 545,476
    Active: 140,808
    Recovered: 394,759
    Death: 9,909
  • Mexico 469,407
    Mexico
    Confirmed: 469,407
    Active: 104,710
    Recovered: 313,386
    Death: 51,311
  • Peru 463,875
    Peru
    Confirmed: 463,875
    Active: 128,894
    Recovered: 314,332
    Death: 20,649
  • Chile 368,825
    Chile
    Confirmed: 368,825
    Active: 16,699
    Recovered: 342,168
    Death: 9,958
  • Spain 361,442
    Spain
    Confirmed: 361,442
    Active: 332,939
    Recovered: ?
    Death: 28,503
  • Iran 324,692
    Iran
    Confirmed: 324,692
    Active: 24,306
    Recovered: 282,122
    Death: 18,264
  • UK 309,005
    UK
    Confirmed: 309,005
    Active: 262,494
    Recovered: ?
    Death: 46,511
  • Saudi Arabia 287,262
    Saudi Arabia
    Confirmed: 287,262
    Active: 33,692
    Recovered: 250,440
    Death: 3,130
  • Pakistan 283,487
    Pakistan
    Confirmed: 283,487
    Active: 17,815
    Recovered: 259,604
    Death: 6,068
  • Bangladesh 255,113
    Bangladesh
    Confirmed: 255,113
    Active: 105,144
    Recovered: 146,604
    Death: 3,365
  • Italy 249,756
    Italy
    Confirmed: 249,756
    Active: 12,924
    Recovered: 201,642
    Death: 35,190
  • Turkey 238,450
    Turkey
    Confirmed: 238,450
    Active: 11,063
    Recovered: 221,574
    Death: 5,813
  • Germany 216,562
    Germany
    Confirmed: 216,562
    Active: 9,905
    Recovered: 197,400
    Death: 9,257
  • France 197,921
    France
    Confirmed: 197,921
    Active: 84,761
    Recovered: 82,836
    Death: 30,324
  • Canada 118,985
    Canada
    Confirmed: 118,985
    Active: 6,580
    Recovered: 103,435
    Death: 8,970
  • China 84,596
    China
    Confirmed: 84,596
    Active: 839
    Recovered: 79,123
    Death: 4,634
  • Netherlands 57,987
    Netherlands
    Confirmed: 57,987
    Active: 51,830
    Recovered: ?
    Death: 6,157
  • Australia 20,698
    Australia
    Confirmed: 20,698
    Active: 9,100
    Recovered: 11,320
    Death: 278
  • S. Korea 14,562
    S. Korea
    Confirmed: 14,562
    Active: 629
    Recovered: 13,629
    Death: 304
  • New Zealand 1,569
    New Zealand
    Confirmed: 1,569
    Active: 23
    Recovered: 1,524
    Death: 22

New machine learning model by MIT comes closer to interpret human emotions

Author at TechGenyz Tech
Computer Emotion Recognition

MIT researchers have developed a new machine learning model that takes computers one step ahead in interpreting human emotions.

The new model can outperform the traditional systems in detecting small facial variations of humans in comprehending mood. It has been taken through a training of thousands of face images.

The model is said to be able to adapt to a group of people with the usage of ‘a little extra training data.’ It is designed upon the combination of a technique of MoE (a mixture of experts) and model personalization techniques.

According to the paper elaborating the model, the technique combo contributed in detecting highly fine-grained facial expression data from people. This was also the first time the two techniques were combined for effective computing.

Experts in MoE are the neural network models that are trained on a processing task producing one output. Along with this was incorporated a gating network for calculating probabilities on which expert can best detect the moods of unseen entities.

The MoEs were personalized for the training providing video recordings from the publicly available RECOLA database that consists of conversations on a video chat platform which is designed for effective computing applications.

18 video recordings were used from the database, with the experts being trained on nine of those, and put to test across the remaining nine. Furthermore, the experts used a residual network called ResNet for object classification.

After additional tests, it was concluded that the models are potent enough to adapt to populations and individuals with very few data. As per the researchers, data based on skin colors are required for making the models more flexible across diverse populations.

One of the ultimate goals of the researchers for these models is to make them capable enough to help computers and robots to learn from small changing data for naturally detecting how humans feel, in order to better serve us.

Career

Subscribe