Results 71 to 80 of about 27,643 (149)

Double weighting convolutional neural net‐works for multi‐view 3D shape recognition

IET Computer Vision, EarlyView., 2022
Abstract Three‐dimensional (3D) object recognition based on multiple views has been a popular area of research in recent years. Existing methods based on the grouping mechanism cannot sensibly group the views. Thus, the 3D shape descriptor that is generated by the final fusion is not representative, and the recognition accuracy still requires ...
Shaohua Qi, Weijun Li, Guowei Yang
wiley   +1 more source

SCEN‐SCADA Security: An Enhanced Osprey Optimization‐Based Cyber Attack Detection Model in Supervisory Control and Data Acquisition System Using Serial Cascaded Ensemble Network

Optimal Control Applications and Methods, EarlyView.
An efficient and accurate cyber attack detection approach with less computational overhead is still a crucial research problem in SCADA. So, a novel and secure model for cyber attack detection in the SCADA system using advanced deep learning techniques together with the heuristic algorithm is executed in this research work. The weighted optimal feature
Fatimah Yaseen Hashim Alzubaidi, Sefer Kurnaz, Raghda Awad Shaban Naseri, Hameed Mutlag Farhan   +3 more
wiley   +1 more source

Multi‐view short‐term photovoltaic power prediction combining satellite images feature learning and graph mutual information feature representation

IET Computer Vision, EarlyView., 2023
This paper explores the cloud information elements of the satellite images from a multi‐view perspective, and performs feature extraction and processing of the meteorological information it contains to learn the impact of cloud cover on photovoltaic (PV) prediction.
Yuxing Dai, Jing Lai, Xuexin Xu, Jianbing Xiahou, Jie Lian, Zhihong Zhang   +5 more
wiley   +1 more source

Novel Calibration Strategy for Kalman Filter‐Based Measurement Fusion Operation to Enhance Aging Monitoring

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This study introduces a novel calibration strategy for the linear Kalman filter (LKF) fusion application in condition monitoring, specifically utilizing accelerated aging data. Unlike the existing literature that often focuses on complex nonlinear Kalman filter variants, this research delves into the calibration of LKF.
Emre Genis, Duygu Bayram Kara
wiley   +1 more source

Q‐fid: Quantum Circuit Fidelity Improvement with LSTM Networks

Advanced Quantum Technologies, EarlyView.
Q‐fid is introduced, an LSTM‐based fidelity prediction system accompanied by a novel metric designed to quantify the fidelity of quantum circuits. This approach frames fidelity prediction as a Time Series Forecasting problem to analyze the tokenized circuits, capturing the causal dependence of the gate sequences and their impact on overall fidelity ...
Yikai Mao, Shaswot Shresthamali, Masaaki Kondo   +2 more
wiley   +1 more source

An integrated approach for mental health assessment using emotion analysis and scales

Healthcare Technology Letters, EarlyView., 2022
For leading a healthy life, a person's mental state is critical. Depression is a prominent cause of mental illness, which could primarily increase early death. It's possible that it's the root of suicidal ideation, and it causes severe impairment in daily life as a result. By detecting human face traits, artificial intelligence has cleared the road for
N. Shanthi, Albert Alexander Stonier, Anli Sherine, T. Devaraju, S. Abinash, R. Ajay, V. Arul Prasath, Vivekananda Ganji   +7 more
wiley   +1 more source

A Hybrid Parameters Estimation Approach for Power Consumption Modeling of Ground Mobile Robots With Unknown Payload

Journal of Field Robotics, EarlyView.
ABSTRACT Typically, batteries are the main power source for mobile robots, and the practical constraints in carrying them pose challenges in achieving efficiency, autonomy, and safety objectives in robotic missions. Moreover, dealing with battery degradation requires a precise understanding of energy consumers' behavior in the system.
Parham Haji Ali Mohamadi, Amin Khorasani, Tom Verstraten, Bram Vanderborght   +3 more
wiley   +1 more source

A scalable transfer learning workflow for extracting biological and behavioural insights from forest elephant vocalizations

Remote Sensing in Ecology and Conservation, EarlyView.
Animal vocalizations encode rich biological information, making bioacoustic analysis a valuable non‐invasive tool for assessing animal welfare and population dynamics. However, traditional methods relying on manual feature selection are labour‐intensive, subjective and lack scalability for the large datasets generated by passive acoustic monitoring ...
Alastair Pickering, Santiago Martinez Balvanera, Kate E. Jones, Daniela Hedwig   +3 more
wiley   +1 more source

Perspectives on water quality analysis emphasizing indexing, modeling, and application of artificial intelligence for comparison and trend forecasting

River, EarlyView.
Abstract Freshwater essential for civilization faces risk from untreated effluents discharged by industries, agriculture, urban areas, and other sources. Increasing demand and abstraction of freshwater deteriorate the pollution scenario more. Hence, water quality analysis (WQA) is an important task for researchers and policymakers to maintain ...
Rijurekha Dasgupta, Subhasish Das, Gourab Banerjee, Asis Mazumdar   +3 more
wiley   +1 more source

Integrating multimodal data and machine learning for entrepreneurship research

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley   +1 more source