Search Results for author:
Found 12 papers, 2 papers with code
PDC & DM-SFT: A Road for LLM SQL Bug-Fix Enhancing
Code Large Language Models (Code LLMs), such as Code llama and DeepSeek-Coder, have demonstrated exceptional performance in the code generation tasks.
BF-Meta: Secure Blockchain-enhanced Privacy-preserving Federated Learning for Metaverse
The metaverse, emerging as a revolutionary platform for social and economic activities, provides various virtual services while posing security and privacy challenges.
Ground-to-UAV sub-Terahertz channel measurement and modeling
Employing experimental measurements through an unmodulated channel setup and a geometry-based stochastic model (GBSM) that integrates three-dimensional positional coordinates and beamwidth, this work evaluates the impact of UAV dynamic movements and antenna orientation on channel performance.
REMAST: Real-time Emotion-based Music Arrangement with Soft Transition
Music as an emotional intervention medium has important applications in scenarios such as music therapy, games, and movies.
Target Detection Framework for Lobster Eye X-Ray Telescopes with Machine Learning Algorithms
Then an algorithm based on morphological operations and two neural networks would be used to detect candidates of celestial objects with different flux from these 2D images.
SongDriver: Real-time Music Accompaniment Generation without Logical Latency nor Exposure Bias
In this paper, we propose SongDriver, a real-time music accompaniment generation system without logical latency nor exposure bias.
Swin-transformer-yolov5 For Real-time Wine Grape Bunch Detection
Results showed that the proposed Swin-T-YOLOv5 outperformed all other studied models for grape bunch detection, with up to 97% of mean Average Precision (mAP) and 0. 89 of F1-score when the weather was cloudy.
Smart obervation method with wide field small aperture telescopes for real time transient detection
The ARGUS uses a deep learning based astronomical detection algorithm implemented in embedded devices in each WFSATs to detect astronomical targets.
Lane detection in complex scenes based on end-to-end neural network
So we combine the advantages of spatial convolution in spatial information processing and the efficiency of ERFNet in semantic segmentation, propose an end-to-end network to lane detection in a variety of complex scenes.
Lane Detection Model Based on Spatio-Temporal Network With Double Convolutional Gated Recurrent Units
One is used to extract the information of the most likely low-level features of lane markings.
Insights into End-to-End Learning Scheme for Language Identification
After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline.
Transitive Distance Clustering with K-Means Duality
We propose a very intuitive and simple approximation for the conventional spectral clustering methods.
