Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A-nesi: A scalable approximate method for probabilistic neurosymbolic inference
We study the problem of combining neural networks with symbolic reasoning. Recently
introduced frameworks for Probabilistic Neurosymbolic Learning (PNL), such as …
introduced frameworks for Probabilistic Neurosymbolic Learning (PNL), such as …
Semantic strengthening of neuro-symbolic learning
Numerous neuro-symbolic approaches have recently been proposed typically with the goal
of adding symbolic knowledge to the output layer of a neural network. Ideally, such losses …
of adding symbolic knowledge to the output layer of a neural network. Ideally, such losses …
Knowledge enhanced neural networks for point cloud semantic segmentation
Deep learning approaches have sparked much interest in the AI community during the last
decade, becoming state-of-the-art in domains such as pattern recognition, computer vision …
decade, becoming state-of-the-art in domains such as pattern recognition, computer vision …
Exploiting t-norms for deep learning in autonomous driving
Deep learning has been at the core of the autonomous driving field development, due to the
neural networks' success in finding patterns in raw data and turning them into accurate …
neural networks' success in finding patterns in raw data and turning them into accurate …
A novel Elman neural network based on Gaussian kernel and improved SOA and its applications
Z Liu, D Ning, J Hou - Expert Systems with Applications, 2024 - Elsevier
To address challenges encountered in traditional Elman neural networks (ENNs), such as
low convergence accuracy, difficulties in hyperparameter selection, and issues with gradient …
low convergence accuracy, difficulties in hyperparameter selection, and issues with gradient …
Uller: A unified language for learning and reasoning
The field of neuro-symbolic artificial intelligence (NeSy), which combines learning and
reasoning, has recently experienced significant growth. There now are a wide variety of …
reasoning, has recently experienced significant growth. There now are a wide variety of …
Bones Can't Be Triangles: Accurate and Efficient Vertebrae Keypoint Estimation Through Collaborative Error Revision
Recent advances in interactive keypoint estimation methods have enhanced accuracy while
minimizing user intervention. However, these methods require user input for error correction …
minimizing user intervention. However, these methods require user input for error correction …
Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints
Synthetic tabular data generation has traditionally been a challenging problem due to the
high complexity of the underlying distributions that characterise this type of data. Despite …
high complexity of the underlying distributions that characterise this type of data. Despite …
[HTML][HTML] Attention-Enhanced Lightweight Architecture with Hybrid Loss for Colposcopic Image Segmentation
Cervical cancer screening through computer-aided diagnosis often faces challenges like
inaccurate segmentation and incomplete boundary detection in colposcopic images. This …
inaccurate segmentation and incomplete boundary detection in colposcopic images. This …
Simple and Effective Transfer Learning for Neuro-Symbolic Integration
Deep Learning (DL) techniques have achieved remarkable successes in recent years.
However, their ability to generalize and execute reasoning tasks remains a challenge. A …
However, their ability to generalize and execute reasoning tasks remains a challenge. A …