Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleAugust 2024JUST ACCEPTED
Multi-model Style-aware Diffusion Learning for Semantic Image Synthesis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Just Accepted https://doi.org/10.1145/3686155Semantic image synthesis aims to generate images from given semantic layouts, which is a challenging task that requires training models to capture the relationship between layouts and images. Previous works are usually based on Generative Adversarial ...
- research-articleJuly 2024
Partial Solution Based Constraint Solving Cache in Symbolic Execution
Proceedings of the ACM on Software Engineering (PACMSE), Volume 1, Issue FSEArticle No.: 110, Pages 2493–2514https://doi.org/10.1145/3660817Constraint solving is one of the main challenges for symbolic execution. Caching is an effective mechanism to reduce the number of the solver invocations in symbolic execution and is adopted by many mainstream symbolic execution engines. However, caching ...
- research-articleJuly 2024
Harmonic resonance and bifurcation of fractional Rayleigh oscillator with distributed time delay
Mathematics and Computers in Simulation (MCSC), Volume 221, Issue CJul 2024, Pages 281–297https://doi.org/10.1016/j.matcom.2024.03.008AbstractResonance and bifurcation are prominent and significant features observed in various nonlinear systems, often leading to catastrophic failure in practical engineering. This paper investigates, under an analytical and numerical perspective, the ...
- research-articleJuly 2024
Optimal fusion of features from decomposed ultrasound RF data with adaptive weighted ensemble classifier to improve breast lesion classification
Image and Vision Computing (IAVC), Volume 146, Issue CJun 2024https://doi.org/10.1016/j.imavis.2024.105045AbstractEarly diagnosis plays a crucial role in successful treatment of breast tumors and reduced mortality. In this study, considering the complementary advantages between features and combined with the improvement of classifiers, fusion of optimal ...
Highlights- The fusion of optimal features from decomposed ultrasound RF data was proposed.
- The FRRI were used to determine the feature set.
- The adaptive weighted ensemble classifier was proposed.
- The proposed methods can help assist ...
- research-articleMay 2024
A Unified Framework for Jointly Compressing Visual and Semantic Data
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 20, Issue 7Article No.: 221, Pages 1–24https://doi.org/10.1145/3654800The rapid advancement of multimedia and imaging technologies has resulted in increasingly diverse visual and semantic data. A large range of applications such as remote-assisted driving requires the amalgamated storage and transmission of various visual ...
-
- research-articleJune 2024
Verification of message-passing uninterpreted programs
Science of Computer Programming (SCPR), Volume 234, Issue CMay 2024https://doi.org/10.1016/j.scico.2023.103075AbstractMessage-passing programs involve several processes with channel-based communications to deal with tasks concurrently. The complex computations and communications between processes make the verification of message-passing programs hard. By ...
Highlights- We provide and prove a decidable subclass of message passing uninterpreted programs.
- We present CFM-based decision procedures for checking message-passing uninterpreted programs.
- We propose a verification framework for message ...
- research-articleMarch 2024
Scene Graph Lossless Compression with Adaptive Prediction for Objects and Relations
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 20, Issue 7Article No.: 196, Pages 1–23https://doi.org/10.1145/3649503The scene graph is a novel data structure describing objects and their pairwise relationship within image scenes. As the size of scene graphs in vision and multimedia applications increases, the need for lossless storage and transmission of such data ...
- research-articleMay 2024
On the properties of kullback-leibler divergence between multivariate Gaussian distributions
NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing SystemsDecember 2023, Article No.: 2535, Pages 58152–58165Kullback-Leibler (KL) divergence is one of the most important measures to calculate the difference between probability distributions. In this paper, we theoretically study several properties of KL divergence between multivariate Gaussian distributions. ...
- research-articleApril 2024
Research on Sensor Anomaly Signal Processing Method Based on Convolutional Neural Network
ICEITSA '23: Proceedings of the 3rd International Conference on Electronic Information Technology and Smart AgricultureDecember 2023, Pages 68–74https://doi.org/10.1145/3641343.3641355The aim of this study is to investigate Convolutional Neural Network (CNN)-based anomaly signal processing methods for sensors in order to improve the detection and prediction performance of anomalous data in complex industrial environments. We analyse ...
- research-articleFebruary 2024
A piecewise temperature-curvature compensation bandgap with internal chopper stabilized amplifiers
Microelectronics Journal (MICROJ), Volume 142, Issue CDec 2023https://doi.org/10.1016/j.mejo.2023.106021AbstractThis paper presented a high-accuracy bandgap reference circuit with novel temperature curvature compensation technology and chopper stabilized technology. The proposed bandgap circuit achieves a good temperature coefficient (TC) without the ...
- ArticleNovember 2023
- research-articleApril 2024
Classification of Red Blood Cell Aggregation Based on Statistical Features of Ultrasonic Radiofrequency Echo Signals and Subspace K-nearest Neighbor Classifier
ISAIMS '23: Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine ScienceOctober 2023, Pages 1096–1100https://doi.org/10.1145/3644116.3644303A red blood cell (RBC) aggregation classification method based on statistical features combination of blood ultrasonic radiofrequency (RF) echo signals and subspace K-nearest neighbor (KNN) classifier is proposed here. The ultrasonic RF echo signals of ...
- research-articleApril 2024
Improved Super-harmonic Imaging of Ultrasound Contrast Agents Based on ICEEMDAN
ISAIMS '23: Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine ScienceOctober 2023, Pages 90–94https://doi.org/10.1145/3644116.3644134Super-harmonics (SH) only come from contrast agents (CA), and the clutter-free SH imaging (SHI) has higher quality in ultrasound CA imaging. How to better separate the SH from echo signals is a key issue to improve the SHI of the CA. The existing three ...
- research-articleApril 2024
The estimation of blood flow velocity profile with the Doppler Ultrasound based on adaptive pulse repetition frequency
ISAIMS '23: Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine ScienceOctober 2023, Pages 26–29https://doi.org/10.1145/3644116.3644123The blood flow velocity profile (BFVP) is associated with atherosclerosis, and the Doppler Ultrasound has wide application in the BFVP estimation. However, the Doppler Ultrasound with autocorrelation technique chooses a fixed and high pulse repetition ...
- ArticleDecember 2023
WDU-Net: Wavelet-Guided Deep Unfolding Network for Image Compressed Sensing Reconstruction
Pattern Recognition and Computer VisionOct 2023, Pages 79–91https://doi.org/10.1007/978-981-99-8537-1_7AbstractMore and more deep unfolding networks have been studied to obtain good interpretability for high-quality image Compressed Sensing (CS) reconstruction. However, most of these networks simply focus on transmitting information across adjacent stages ...
- ArticleOctober 2023
CCMOP: A Runtime Verification Tool for C/C++ Programs
AbstractRuntime verification (RV) is an effective lightweight formal method for improving software’s reliability at runtime. There exist no RV tools specially designed for C++ programs. This paper introduces the first one, i.e., CCMOP, which implements an ...
- research-articleOctober 2023
A weak current detection circuit with LDO for electrochemical sensors
Microelectronics Journal (MICROJ), Volume 140, Issue COct 2023https://doi.org/10.1016/j.mejo.2023.105925AbstractElectrochemical sensors applied in single molecules detection can only trigger a weak pA-level current, which is hard to detect. In this paper, a weak current detection circuit with LDO for electrochemical sensors is presented to ...
- research-articleOctober 2023
Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning
Artificial Intelligence in Medicine (AIIM), Volume 144, Issue COct 2023https://doi.org/10.1016/j.artmed.2023.102664AbstractAccurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of parameter settings, the autocorrelation velocimetry methods based on clutter filtering are ...
Highlights- Integrates clutter filtering and blood flow velocimetry into a single neural network model
- Can be applied directly to Doppler echo signals without IQ demodulation
- Uses the Field II platform to generate data to train the model
- ...
- ArticleOctober 2023
Edge-Guided Interpretable Neural Network for Image Compressive Sensing Reconstruction
AbstractIn recent years, interpretable Compressive Sensing (CS) technology has received more and more attention. Although these CS reconstruction methods can obtain good interpretability, they ignore the importance of edge information, which greatly ...
- research-articleAugust 2023
Kullback-Leibler Divergence-Based Out-of-Distribution Detection With Flow-Based Generative Models
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 36, Issue 4April 2024, Pages 1683–1697https://doi.org/10.1109/TKDE.2023.3309853Recent research has revealed that deep generative models including flow-based models and Variational Autoencoders may assign higher likelihoods to out-of-distribution (OOD) data than in-distribution (ID) data. However, we cannot sample OOD data from the ...