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Found 10 papers, 5 papers with code
Real-Time Fault Detection and Process Control Based on Multi-channel Sensor Data Fusion
Sensor signals acquired in the industrial process contain rich information which can be analyzed to facilitate effective monitoring of the process, early detection of system anomalies, quick diagnosis of fault root causes, and intelligent system design and control.
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications
To resolve this, we propose a new structure learning algorithm LEAST, which comprehensively fulfills our business requirements as it attains high accuracy, efficiency and scalability at the same time.
A Person Re-identification Data Augmentation Method with Adversarial Defense Effect
This method can not only improve the accuracy of the model, but also help the model defend against adversarial examples; 2) Multi-Modal Defense, it integrates three homogeneous modal images of visible, grayscale and sketch, and further strengthens the defense ability of the model.
Ranked #19 on
Person Re-Identification
on Market-1501-C
Canted antiferromagnetic order and spin dynamics in the honeycomb-lattice Tb2Ir3Ga9
Despite the $J_{{\rm eff}}=1/2$ moments, the spin Hamiltonian is denominated by a large in-plane anisotropy $K_z \sim -1$ meV.
Strongly Correlated Electrons Materials Science
Fast Newton method solving KLR based on Multilevel Circulant Matrix with log-linear complexity
Specifically, by approximating the kernel matrix with an MCM, the storage space is reduced to $O(n)$, and further approximating the coefficient matrix of the Newton equation as MCM, the computational complexity of Newton iteration is reduced to $O(n \log n)$.
DSCA: A Dual-Stream Network with Cross-Attention on Whole-Slide Image Pyramids for Cancer Prognosis
Our experiments and ablation studies verify that (i) the proposed DSCA could outperform existing state-of-the-art methods in cancer prognosis, by an average C-Index improvement of around 4. 6%; (ii) our DSCA network is more efficient in computation -- it has more learnable parameters (6. 31M vs. 860. 18K) but less computational costs (2. 51G vs. 4. 94G), compared to a typical existing multi-resolution network.
Multilevel Transformer For Multimodal Emotion Recognition
Inspired by Transformer TTS, we propose a multilevel transformer model to perform fine-grained multimodal emotion recognition.
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images
To tackle these problems, we propose a novel adversarial multiple instance learning (AdvMIL) framework.
Learning to Compress Unmanned Aerial Vehicle (UAV) Captured Video: Benchmark and Analysis
During the past decade, the Unmanned-Aerial-Vehicles (UAVs) have attracted increasing attention due to their flexible, extensive, and dynamic space-sensing capabilities.
Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification
Experimental results show that PseMix could often assist state-of-the-art MIL networks to refresh their classification performance on WSIs.
