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Activity Recognition within a Manufacturing System: A Comparison of Logic Programming, Machine Learning, and Combinatorial Optimization Based Methods

https://doi.org/10.2139/ssrn.4792141
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Event Processing for Maritime Situational Awareness
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Temporal Convolutional Networks: A Unified Approach to Action Segmentation
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Fault diagnosis in power transformers using multi-class logical analysis of data
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Probabilistic (logic) programming concepts
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General mathematical programming formulations for the statistical classification problem
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Logic programming and knowledge representation
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Optimization approaches to Supervised Classification
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A hyperbox classifier model for identifying secure carbon dioxide reservoirs
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From action to activity: Sensor-based activity recognition
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Semantic human activity recognition: A literature review
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Evaluating the performance of a discrete manufacturing process using RFID: A case study
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Prediction of folding type of proteins using mixed-integer linear programming
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A probabilistic logic programming event calculus
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Random Forests
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A review of some techniques for inclusion of domain-knowledge into deep neural networks
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Classification and disease prediction via mathematical programming
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Mining frequent trajectory patterns of WIP in Internet of Things-based spatial-temporal database
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Multicategory discrimination via linear programming
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A Data Mining Framework for Massive RFID Data Based on Apriori Algorithm
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An Overview of Overfitting and its Solutions
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Joint action recognition and pose estimation from video
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Convolutional Two-Stream Network Fusion for Video Action Recognition
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Trajectory Prediction of Humans in Factories and Warehouses with Real-Time Locating Systems
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Learning Spatiotemporal Features with 3D Convolutional Networks
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STM: SpatioTemporal and Motion Encoding for Action Recognition
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Activity recognition from acceleration data using AR model representation and SVM
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Human Activity Recognition with User-Free Accelerometers in the Sensor Networks
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Learning Optimal Fair Scoring Systems for Multi-Class Classification
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Deep Dilated Convolution on Multimodality Time Series for Human Activity Recognition
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A Survey on Indoor Positioning Systems for IoT-Based Applications
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A Novel Multi-Stage Training Approach for Human Activity Recognition From Multimodal Wearable Sensor Data Using Deep Neural Network
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Human Activity Recognition From Multi-modal Wearable Sensor Data Using Deep Multi-stage LSTM Architecture Based on Temporal Feature Aggregation
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An Ontology-Based Hybrid Approach to Activity Modeling for Smart Homes
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Sequential Weakly Labeled Multiactivity Localization and Recognition on Wearable Sensors Using Recurrent Attention Networks
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Nearest neighbor pattern classification
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An Event Calculus for Event Recognition
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A model for reasoning about persistence and causation
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THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
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A Data Mining Trajectory Clustering Methodology for Modeling Indoor Design Space Utilization
inferredcites →https://doi.org/10.1145/1922649.1922653openalex-extracted
Human activity analysis
inferredcites →https://doi.org/10.1145/3161174openalex-extracted
Multimodal Deep Learning for Activity and Context Recognition
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Multi-task Self-Supervised Learning for Human Activity Detection
inferredcites →https://doi.org/10.1145/3447548.3467401openalex-extracted
A Transformer-based Framework for Multivariate Time Series Representation Learning
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Anomaly Detection in a Boxed Beef Supply Chain
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TrajFormer: Efficient Trajectory Classification with Transformers
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COCOA
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Algorithm = logic + control
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Long Short-Term Memory
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Classification and Disease Prediction via Mathematical Programming
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Classification and Regression via Integer Optimization
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Two-Stream Convolution Augmented Transformer for Human Activity Recognition
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Differentiable Inductive Logic Programming for Structured Examples
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Learning Explanatory Rules from Noisy Data
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AttnSense: Multi-level Attention Mechanism For Multimodal Human Activity Recognition
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Layout and Material Flow Optimization in Digital Factory
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Motion Capture Technology in Industrial Applications: A Systematic Review
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Bottom-Up Stratified Probabilistic Logic Programming with Fusemate
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Exploiting Generative AI to Scale up Intelligent Tutoring Systems
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On the difficulty of training Recurrent Neural Networks
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Deep Neural Networks as 0-1 Mixed Integer Linear Programs: A Feasibility Study
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DeepProbLog: Neural Probabilistic Logic Programming
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Neural Logic Reinforcement Learning
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Partition-based formulations for mixed-integer optimization of trained ReLU neural networks
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Multi-Stage Based Feature Fusion of Multi-Modal Data for Human Activity Recognition
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Neuro-Symbolic Approaches for Context-Aware Human Activity Recognition
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Semantic Probabilistic Layers for Neuro-Symbolic Learning
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