T N Manjunath
Biographic Data
| ID | 8425616 |
|---|---|
| NAME | T N Manjunath |
| GIVEN NAMES | T N |
| FAMILY NAME | Manjunath |
| SIGNATURE | MANJUNATH T N |
| AFFILIATIONS | ESI - Post Graduate Institute of Medical Science and Research |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Human activity recognition using CNN and long term short term memory
Human activity recognition aims to work out the activities performed by someone in a picture or video. Examples of actions are running, sitting, sleeping, and standing. Complex movement patterns and harmful occurrences like falling may be a part of these activities. The suggested ConvLSTM network can be created by successively combining fully connected layers, long immediate memory (LSTM) networks, and convolutional neural networks (CNN). The acq…
A survey on human activity recognition using CNN and LSTM
Human Activity Recognition (HAR) plays a massive role inside the everyday life of people due to its capability to investigate tremendous high-degree data approximately human interest from wearable or stationary devices. An extensive quantity of studies has been completed on HAR and numerous techniques primarily based on deep gaining knowledge of and device analyzing were exploited through the research community to categorize human sports. The pri…
No prominent works on this page.
Human activity recognition using CNN and long term short term memory
Human activity recognition aims to work out the activities performed by someone in a picture or video. Examples of actions are running, sitting, sleeping, and standing. Complex movement patterns and harmful occurrences like falling may be a part of these activities. The suggested ConvLSTM network can be created by successively combining fully connected layers, long immediate memory (LSTM) networks, and convolutional neural networks (CNN). The acq…
A survey on human activity recognition using CNN and LSTM
Human Activity Recognition (HAR) plays a massive role inside the everyday life of people due to its capability to investigate tremendous high-degree data approximately human interest from wearable or stationary devices. An extensive quantity of studies has been completed on HAR and numerous techniques primarily based on deep gaining knowledge of and device analyzing were exploited through the research community to categorize human sports. The pri…
Artificial Intelligence (2 works) · Computer Science (2 works) · Context-Aware Activity Recognition Systems (2 works) · Convolutional neural network (2 works) · Anomaly Detection Techniques and Applications (1 work) · Categorization (1 work) · Computer vision (1 work) · Data science (1 work) · Deep learning (1 work) · Human Pose and Action Recognition (1 work)