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Found 36 papers, 8 papers with code
Distributed Data-driven Unknown-input Observers
Moving to a data-driven approach, it is shown that the input/output/state trajectories of the system are compatible with the equations of a D-DUIO, and this allows, under suitable assumptions, to express the matrices of a possible DUIO in terms of the matrices of pre-collected data.
Robust Control of Unknown Switched Linear Systems from Noisy Data
This paper investigates the problem of data-driven stabilization for linear discrete-time switched systems with unknown switching dynamics.
A quantum segmentation algorithm based on local adaptive threshold for NEQR image
In this paper, a quantum segmentation algorithm based on local adaptive threshold for NEQR image is proposed, which can use quantum mechanism to simultaneously compute local thresholds for all pixels in a gray-scale image and quickly segment the image into a binary image.
Quantum Image Segmentation Based on Grayscale Morphology
The classical image segmentation algorithm based on grayscale morphology can effectively segment images with uneven illumination, but with the increase of the image data, the real-time problem will emerge.
Quantum-Based Feature Selection for Multi-classification Problem in Complex Systems with Edge Computing
The complex systems with edge computing require a huge amount of multi-feature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational efficiency and save the resource consumption.
A quantum moving target segmentation algorithm for grayscale video
For a quantum video with $2^m$ frames (every frame is a $2^n\times 2^n$ image with $q$ grayscale levels), the complexity of our algorithm can be reduced to O$(n^2 + q)$.
Quantum image edge detection based on eight-direction Sobel operator for NEQR
However, the existing QSED algorithms only consider two- or four-direction Sobel operator, which leads to a certain loss of edge detail information in some high-definition images.
A quantum system control method based on enhanced reinforcement learning
Traditional quantum system control methods often face different constraints, and are easy to cause both leakage and stochastic control errors under the condition of limited resources.
A hybrid quantum-classical conditional generative adversarial network algorithm for human-centered paradigm in cloud
In order to solve these problems, a hybrid quantum-classical conditional generative adversarial network (QCGAN) algorithm is proposed, which is a knowledge-driven human-computer interaction computing mode that can be implemented in cloud.
A Quantum States Preparation Method Based on Difference-Driven Reinforcement Learning
To solve the above problems, a difference-driven reinforcement learning (RL) algorithm for quantum state preparation of two-qubit system is proposed by improving the reward function and action selection strategy.
Solving Low-Dose CT Reconstruction via GAN with Local Coherence
The Computed Tomography (CT) for diagnosis of lesions in human internal organs is one of the most fundamental topics in medical imaging.
A Unitary Weights Based One-Iteration Quantum Perceptron Algorithm for Non-Ideal Training Sets
In order to solve the problem of non-ideal training sets (i. e., the less-complete or over-complete sets) and implement one-iteration learning, a novel efficient quantum perceptron algorithm based on unitary weights is proposed, where the singular value decomposition of the total weight matrix from the training set is calculated to make the weight matrix to be unitary.
A Block-Ring connected Topology of Parameterized Quantum Circuits
Compared with the pure all-to-all topology circuits which own the best power, BR topology have similar performance and the number of parameters and 2-qubit gate reduced from 0(n^2) to 0(mn) , m is a hyperparameter set by ourselves.
Data-driven Polytopic Output Synchronization of Heterogeneous Multi-agent Systems from Noisy Data
This method utilizes measured data and a noise-matrix polytope to ensure near-optimal output synchronization.
Multi-stage Progressive Reasoning for Dunhuang Murals Inpainting
The execution of the model is similar to the process of a mural restorer (i. e., inpainting the structure of the damaged mural globally first and then adding the local texture details further).
Shadow Removal of Text Document Images Using Background Estimation and Adaptive Text Enhancement
Thirdly, we propose an adaptive text contrast enhancement strategy to generate shadow-free results with comfortable visual perception across shadow and non-shadow regions.
Learning Robust Data-based LQG Controllers from Noisy Data
In this work, a data-based formulation for computing the steady-state Kalman gain is proposed based on semi-definite programming (SDP) using some noise-free input-state-output data.
Self-triggered Resilient Stabilization of Linear Systems with Quantized Output
If, in addition, the transmission protocols at the controller-to-actuator (C-A) and sensor-to-controller (S-C) channels can be adapted, the self-triggered control architecture can be considerably simplified, leveraging a delicate observer-based deadbeat controller to eliminate the need for running the controller in parallel at the encoder side.
Towards Accurate Acne Detection via Decoupled Sequential Detection Head
In addition, we build a high-quality acne detection dataset named ACNE-DET to verify the effectiveness of DSDH.
Elevation Estimation-Driven Building 3D Reconstruction from Single-View Remote Sensing Imagery
Our Building3D is rooted in the SFFDE network for building elevation prediction, synchronized with a building extraction network for building masks, and then sequentially performs point cloud reconstruction, surface reconstruction (or CityGML model reconstruction).
An advanced YOLOv3 method for small object detection
Small object detection has important application value in the fields of autonomous driving and drone scene analysis.
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition
In this paper, we propose SoftCorrect with a soft error detection mechanism to avoid the limitations of both explicit and implicit error detection.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Mask the Correct Tokens: An Embarrassingly Simple Approach for Error Correction
Since the error rate of the incorrect sentence is usually low (e. g., 10\%), the correction model can only learn to correct on limited error tokens but trivially copy on most tokens (correct tokens), which harms the effective training of error correction.
Coresets for Wasserstein Distributionally Robust Optimization Problems
Though it is challenging to obtain a conventional coreset for \textsf{WDRO} due to the uncertainty issue of ambiguous data, we show that we can compute a ``dual coreset'' by using the strong duality property of \textsf{WDRO}.
A Data-dependent Approach for High Dimensional (Robust) Wasserstein Alignment
Our framework is a ``data-dependent'' approach that has the complexity depending on the intrinsic dimension of the input data.
Data-driven Self-triggered Control via Trajectory Prediction
Self-triggered control, a well-documented technique for reducing the communication overhead while ensuring desired system performance, is gaining increasing popularity.
A Novel Sequential Coreset Method for Gradient Descent Algorithms
A wide range of optimization problems arising in machine learning can be solved by gradient descent algorithms, and a central question in this area is how to efficiently compress a large-scale dataset so as to reduce the computational complexity.
Data-Driven Resilient Predictive Control under Denial-of-Service
Finally, a numerical example is given to validate the effectiveness of the proposed control method.
FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition
Although multiple candidates are generated by an ASR system through beam search, current error correction approaches can only correct one sentence at a time, failing to leverage the voting effect from multiple candidates to better detect and correct error tokens.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
UAV-aided Radio Map Construction Exploiting Environment Semantics
This paper constructs a full dimensional (6D) radio map to predict the channel gain between any transmitter location and any receiver location based on received signal strength (RSS) measurements between low-altitude aerial nodes and ground nodes.
Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol
When both input and output channels are subject to DoS attacks and quantization, the proposed structure is shown able to decouple the encoding schemes for input, output, and estimated output signals.
Is Simple Uniform Sampling Effective for Center-Based Clustering with Outliers: When and Why?
Real-world datasets often contain outliers, and the presence of outliers can make the clustering problems to be much more challenging.
Feature Fusion through Multitask CNN for Large-scale Remote Sensing Image Segmentation
In recent years, Fully Convolutional Networks (FCN) has been widely used in various semantic segmentation tasks, including multi-modal remote sensing imagery.
ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention
Semantic Evaluation (SemEval) 2018 Task 12 {``}The Argument Reasoning Comprehension{''} committed to research natural language reasoning.
DeepUNet: A Deep Fully Convolutional Network for Pixel-level Sea-Land Segmentation
Semantic segmentation is a fundamental research in remote sensing image processing.
ITNLP-AiKF at SemEval-2017 Task 1: Rich Features Based SVR for Semantic Textual Similarity Computing
Semantic Textual Similarity (STS) devotes to measuring the degree of equivalence in the underlying semantic of the sentence pair.
