Results 21 to 30 of about 218,805 (280)
IEEE Access, 2023 Prediction of work Travel mode choice is one of the most important parts of travel demand forecasting. Planners can achieve sustainability goals by accurately forecasting how people will get to and from work.
Mahdi Aghaabbasi +4 more
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Frugal Optimization for Cost-related Hyperparameters
, 2020 The increasing demand for democratizing machine learning algorithms calls for hyperparameter optimization (HPO) solutions at low cost. Many machine learning algorithms have hyperparameters which can cause a large variation in the training cost.
Huang, Silu, Wang, Chi, Wu, Qingyun
core +2 more sources
Bayesian off-line detection of multiple change-points corrupted by multiplicative noise : application to SAR image edge detection [PDF]
, 2003 This paper addresses the problem of Bayesian off-line change-point detection in synthetic aperture radar images. The minimum mean square error and maximum a posteriori estimators of the changepoint positions are studied.
Andre-Obrecht +39 more
core +3 more sources
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL
, 2022 The performance of reinforcement learning (RL) agents is sensitive to the choice of hyperparameters. In real-world settings like robotics or industrial control systems, however, testing different hyperparameter configurations directly on the environment can be financially prohibitive, dangerous, or time consuming.
Wang, Han +9 more
openaire +2 more sources
Nonlinear Hyperparameter Optimization of a Neural Network in Image Processing for Micromachines
Micromachines, 2021 Deep neural networks are widely used in the field of image processing for micromachines, such as in 3D shape detection in microelectronic high-speed dispensing and object detection in microrobots.
Mingming Shen +4 more
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Mathematics, 2022 Over the past few decades, convolutional neural networks (CNNs) have achieved outstanding results in addressing a broad scope of computer vision problems.
Rogeany Kanza +4 more
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Sensors, 2023 Pervasive computing, human–computer interaction, human behavior analysis, and human activity recognition (HAR) fields have grown significantly. Deep learning (DL)-based techniques have recently been effectively used to predict various human actions using
Shaik Jameer, Hussain Syed
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IEEE Access, 2023 Non-traumatic grief can be defined as, a complex process that includes emotional, physical, spiritual, social, and intellectual behaviors and responses through which individuals, families, and communities incorporate actual, anticipated, or perceived ...
Jacinto Mata-Vazquez +4 more
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Comparative Analysis of Transformers to Support Fine-Grained Emotion Detection in Short-Text Data
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Understanding a person’s mood and circumstances by way of sentiment or finer-grained emotion detection can play a significant role in AI systems and applications, such as in chat dialogue or reviews.
Robert H. Frye, David C. Wilson
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BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework
Frontiers in Computational Neuroscience, 2020 Human intelligence is constituted by a multitude of cognitive functions activated either directly or indirectly by external stimuli of various kinds. Computational approaches to the cognitive sciences and to neuroscience are partly premised on the idea ...
Newton Howard +6 more
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