35 citations · 102 across the 51 of their papers we have counts for
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Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets
Daniel Geissler, Dominique Nshimyimana, Vitor Fortes Rey +3
The research of machine learning (ML) algorithms for human activity recognition (HAR) has made significant progress with publicly available datasets. However, most research priorit…
Spend More to Save More (SM2): An Energy-Aware Implementation of Successive Halving for Sustainable Hyperparameter Optimization
Daniel Geissler, Bo Zhou, Sungho Suh +1
A fundamental step in the development of machine learning models commonly involves the tuning of hyperparameters, often leading to multiple model training runs to work out the best…
TSAK: Two-Stage Semantic-Aware Knowledge Distillation for Efficient Wearable Modality and Model Optimization in Manufacturing Lines
Hymalai Bello, Daniel Geißler, Sungho Suh +2
Smaller machine learning models, with less complex architectures and sensor inputs, can benefit wearable sensor-based human activity recognition (HAR) systems in many ways, from co…
BeSound: Bluetooth-Based Position Estimation Enhancing with Cross-Modality Distillation
Hymalai Bello, Sungho Suh, Bo Zhou +1
Smart factories leverage advanced technologies to optimize manufacturing processes and enhance efficiency. Implementing worker tracking systems, primarily through camera-based meth…
Text me the data: Generating Ground Pressure Sequence from Textual Descriptions for HAR
Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh +3
In human activity recognition (HAR), the availability of substantial ground truth is necessary for training efficient models. However, acquiring ground pressure data through physic…
The Power of Training: How Different Neural Network Setups Influence the Energy Demand
Daniel Geißler, Bo Zhou, Mengxi Liu +2
This work offers a heuristic evaluation of the effects of variations in machine learning training regimes and learning paradigms on the energy consumption of computing, especially…
Remaining useful life prediction of Lithium-ion batteries using spatio-temporal multimodal attention networks
Sungho Suh, Dhruv Aditya Mittal, Hymalai Bello +3
Lithium-ion batteries are widely used in various applications, including electric vehicles and renewable energy storage. The prediction of the remaining useful life (RUL) of batter…
Two-stage Early Prediction Framework of Remaining Useful Life for Lithium-ion Batteries
Dhruv Mittal, Hymalai Bello, Bo Zhou +3
Early prediction of remaining useful life (RUL) is crucial for effective battery management across various industries, ranging from household appliances to large-scale applications…
Worker Activity Recognition in Manufacturing Line Using Near-body Electric Field
Sungho Suh, Vitor Fortes Rey, Sizhen Bian +5
Manufacturing industries strive to improve production efficiency and product quality by deploying advanced sensing and control systems. Wearable sensors are emerging as a promising…
CaptAinGlove: Capacitive and Inertial Fusion-Based Glove for Real-Time on Edge Hand Gesture Recognition for Drone Control
Hymalai Bello, Sungho Suh, Daniel Geißler +3
We present CaptAinGlove, a textile-based, low-power (1.15Watts), privacy-conscious, real-time on-the-edge (RTE) glove-based solution with a tiny memory footprint (2MB), designed to…
Non-destructive Fault Diagnosis of Electronic Interconnects by Learning Signal Patterns of Reflection Coefficient in the Frequency Domain
Tae Yeob Kang, Haebom Lee, Sungho Suh
Fault detection and diagnosis of the interconnects are crucial for prognostics and health management (PHM) of electronics. Traditional methods, which rely on electronic signals as…
InMyFace: Inertial and Mechanomyography-Based Sensor Fusion for Wearable Facial Activity Recognition
Hymalai Bello, Luis Alfredo Sanchez Marin, Sungho Suh +2
Recognizing facial activity is a well-understood (but non-trivial) computer vision problem. However, reliable solutions require a camera with a good view of the face, which is ofte…
Learning from the Best: Contrastive Representations Learning Across Sensor Locations for Wearable Activity Recognition
Vitor Fortes Rey, Sungho Suh, Paul Lukowicz
We address the well-known wearable activity recognition problem of having to work with sensors that are non-optimal in terms of information they provide but have to be used due to…
Smart-Badge: A wearable badge with multi-modal sensors for kitchen activity recognition
Mengxi Liu, Sungho Suh, Bo Zhou +2
Human health is closely associated with their daily behavior and environment. However, keeping a healthy lifestyle is still challenging for most people as it is difficult to recogn…
Generalized multiscale feature extraction for remaining useful life prediction of bearings with generative adversarial networks
Sungho Suh, Paul Lukowicz, Yong Oh Lee
Bearing is a key component in industrial machinery and its failure may lead to unwanted downtime and economic loss. Hence, it is necessary to predict the remaining useful life (RUL…
Sequential Targeting: an incremental learning approach for data imbalance in text classification
Joel Jang, Yoonjeon Kim, Kyoungho Choi +1
Classification tasks require a balanced distribution of data to ensure the learner to be trained to generalize over all classes. In real-world datasets, however, the number of inst…