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TricP: A Novel Approach for Human Activity Recognition Using Tricky Predator Optimization Approach Based on Inception and LSTM

https://doi.org/10.2139/ssrn.4715646
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00521-018-3627-6openalex-extracted
Improved inception-residual convolutional neural network for object recognition
inferredcites →https://doi.org/10.1007/s00607-021-00928-8openalex-extracted
Multi-input CNN-GRU based human activity recognition using wearable sensors
inferredcites →https://doi.org/10.1007/s11554-021-01114-xopenalex-extracted
Temporal and spatial feature based approaches in drowsiness detection using deep learning technique
inferredcites →https://doi.org/10.1007/s42979-020-00143-wopenalex-extracted
Performance Analysis of Inception-v2 and Yolov3-Based Human Activity Recognition in Videos
inferredcites →https://doi.org/10.1007/s42979-021-00576-xopenalex-extracted
Sparse Deep LSTMs with Convolutional Attention for Human Action Recognition
inferredcites →https://doi.org/10.1016/j.eswa.2020.114107openalex-extracted
Red fox optimization algorithm
inferredcites →https://doi.org/10.1016/j.image.2018.09.003openalex-extracted
TS-LSTM and temporal-inception: Exploiting spatiotemporal dynamics for activity recognition
inferredcites →https://doi.org/10.1016/j.knosys.2021.106918openalex-extracted
Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization
inferredcites →https://doi.org/10.1016/j.neucom.2020.01.125openalex-extracted
An ensemble of autonomous auto-encoders for human activity recognition
inferredcites →https://doi.org/10.1088/1742-6596/1921/1/012074openalex-extracted
Human Anomalous Activity Detection: Shape and Motion Approach in Crowded Scenes
inferredcites →https://doi.org/10.1088/1757-899x/790/1/012145openalex-extracted
Dynamic Facial Expression Recognition Based on ResNet and LSTM
inferredcites →https://doi.org/10.1109/access.2018.2890675openalex-extracted
InnoHAR: A Deep Neural Network for Complex Human Activity Recognition
inferredcites →https://doi.org/10.1109/access.2020.2982225openalex-extracted
LSTM-CNN Architecture for Human Activity Recognition
inferredcites →https://doi.org/10.1109/access.2021.3078184openalex-extracted
iSPLInception: An Inception-ResNet Deep Learning Architecture for Human Activity Recognition
inferredcites →https://doi.org/10.1109/cec.2018.8477769openalex-extracted
Coyote Optimization Algorithm: A New Metaheuristic for Global Optimization Problems
inferredcites →https://doi.org/10.1109/icet48972.2019.8994412openalex-extracted
Human Activity Recognition using Multi-Head CNN followed by LSTM
inferredcites →https://doi.org/10.1109/icsec53205.2021.9684590openalex-extracted
Blister Package Classification Using ResNet-101 for Identification of Medication
inferredcites →https://doi.org/10.1109/tie.2020.3028796openalex-extracted
Rider-Deep-LSTM Network for Hybrid Distance Score-Based Fault Prediction in Analog Circuits
inferredcites →https://doi.org/10.1186/s13640-020-00544-0openalex-extracted
Human activity prediction using saliency-aware motion enhancement and weighted LSTM network
inferredcites →https://doi.org/10.3390/app11052188openalex-extracted
Human Activity Recognition through Recurrent Neural Networks for Human–Robot Interaction in Agriculture
inferredcites →https://doi.org/10.3390/app11062675openalex-extracted
Deep Learning Based Human Activity Recognition Using Spatio-Temporal Image Formation of Skeleton Joints
inferredcites →https://doi.org/10.3390/electronics10030308openalex-extracted
Biometric User Identification Based on Human Activity Recognition Using Wearable Sensors: An Experiment Using Deep Learning Models
inferredcites →https://doi.org/10.3390/s21020654openalex-extracted
Moving the Lab into the Mountains: A Pilot Study of Human Activity Recognition in Unstructured Environments
inferredcites →https://doi.org/10.3390/s21062141openalex-extracted
Sensor-Based Human Activity Recognition with Spatio-Temporal Deep Learning
inferredcites →https://doi.org/10.3390/s21082814openalex-extracted
New Sensor Data Structuring for Deeper Feature Extraction in Human Activity Recognition
inferredcites →https://doi.org/10.37965/jait.2020.0051openalex-extracted
Human Activity Recognition and Embedded Application Based on Convolutional Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1909.05622openalex-extracted
Inception-inspired LSTM for Next-frame Video Prediction
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