Research and Application of Fine-Grained Image Classification Based on Small Collar Dataset

Article Computer Science, Artificial Intelligence

An L1-and-L2-Norm-Oriented Latent Factor Model for Recommender Systems

Di Wu et al.

Summary: This article introduces a novel LF model that combines the characteristics of L1 and L2 norms to improve accuracy and stability in handling HiDS data with outliers. Experimental results demonstrate that the model outperforms state-of-the-art models in predicting missing data, indicating its potential for real-world HiDS data applications.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2022)

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Article Computer Science, Artificial Intelligence

A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction

Di Wu et al.

Summary: This paper proposes a data-characteristic-aware latent factor (DCALF) model for highly accurate QoS predictions. By appropriately implementing predictions based on the characteristics of given QoS data and detecting user and service neighborhoods and noises, the model outperforms existing QoS predictors and is highly competitive in the field of Web service selection and recommendation.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2022)

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Article Automation & Control Systems

Rotated Sphere Haar Wavelet and Deep Contractive Auto-Encoder Network With Fuzzy Gaussian SVM for Pilot's Pupil Center Detection

Edmond Q. Wu et al.

Summary: This paper proposes a new method to solve the challenge of tracking pilot attention by integrating spherical Haar wavelet transform and deep learning methods. The method includes feature learning, spherical Haar wavelet, higher contractive autoencoder, and fuzzy Gaussian support vector machine components. The experimental results show the effectiveness of the model for spherical signal detection.

IEEE TRANSACTIONS ON CYBERNETICS (2021)

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Article Automation & Control Systems

Nonparametric Bayesian Prior Inducing Deep Network for Automatic Detection of Cognitive Status

Edmond Q. Wu et al.

Summary: In this article, a gamma deep belief network is proposed to recognize pilots' brain fatigue status by extracting cognitive features and identifying fatigue characteristics. Experimental results show that the model achieves satisfactory results in terms of both recognition accuracy and stability.

IEEE TRANSACTIONS ON CYBERNETICS (2021)

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Article Computer Science, Artificial Intelligence

Person Reidentification by Multiscale Feature Representation Learning With Random Batch Feature Mask

Yong Wu et al.

Summary: This study proposes a deep model for Person reidentification (PReID) that combines multiscale feature representation learning (MFRL) and random batch feature mask (RBFM). By utilizing two identity losses to supervise the learning of small-scale and large-scale features, as well as introducing the RBFM branch to learn local feature representations, the effectiveness of the model is enhanced.

IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS (2021)

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Article Automation & Control Systems

A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems

Di Wu et al.

Summary: The paper proposes a deep latent factor model (DLFM) for building a deep-structured RS efficiently on a high-dimensional and sparse matrix, by sequentially connecting multiple latent factor models to construct a deep-structured model. The experimental results show that DLFM can balance prediction accuracy and computational efficiency better than state-of-the-art models, meeting the industrial RS's need for fast and accurate recommendations.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2021)

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Article Engineering, Multidisciplinary