Recent trends in machine learning for human activity recognition—A survey

By Sreenivasan Ramasamy Ramamurthy, Nirmalya Roy. WIREs Data Mining Knowl. Discov., 2018

300 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/5002aa2c446f50cdf8e0c17bc833e302bfc100b3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Thinagaran Perumal
2. Sakorn Mekruksavanich
3. Anuchit Jitpattanakul

In Computer Vision and Pattern Recognition

1. Thinagaran Perumal
2. S. Padmavathi
3. Sakorn Mekruksavanich
4. Anuchit Jitpattanakul
5. Elangovan Ramanujam

In Signal Processing

1. Sakorn Mekruksavanich
2. Anuchit Jitpattanakul

Citations in the corpus

• LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes (2021, methodology): “Traditional methods have made major strides through the implementation of state-of-the-art deep-learning techniques, including decision tree, naïve Bayes, support vector machine [21], and artificial neural networks [22].”
• Human Activity Recognition With Smartphone and Wearable Sensors Using Deep Learning Techniques: A Review (2021, background): “…solutions have successfully achieved HAR recognition activities during the last decade, but they face certain challenges in certain cases like [7]–[9]. i Limited amount of training data for multiclass activity recognition ii Recognizing arbitrary and complex features using handcrafted/manual…”