Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by lighting conditions. As commercial confidentiality and personal privacy become increasingly paramount, access to training samples is often restricted. ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Traditional convolutional neural networks (CNNs) struggle with scale and rotation transformations, resulting in reduced performance on transformed images. Previous research focused on designing specific CNN modules to extract transformation-invariant...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Cluster analysis, as a core technique in unsupervised learning, has widespread applications. With the increasing complexity of data, deep clustering, which integrates the advantages of deep learning and traditional clustering algorithms, demonstrates...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
The significant computational demands of Deep Neural Networks (DNNs) present a major challenge for their practical application. Recently, many Application-Specific Integrated Circuit (ASIC) chips have incorporated dedicated hardware support for neura...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Time series anomaly detection is crucial for maintaining stable systems. Existing methods face two main challenges. First, it is difficult to directly model the dependencies of diverse and complex patterns within the sequences. Second, many methods t...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Graph embedding aims to embed the information of graph data into low-dimensional representation space. Prior methods generally suffer from an imbalance of preserving structural information and node features due to their pre-defined inductive biases, ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Recently, transformer-based methods have shown remarkable success in object re-identification. However, most works directly embed off-the-shelf transformer backbones for feature extraction. These methods treat all patch tokens equally, ignoring the d...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Artificial neural networks (ANNs) were originally modeled after their biological counterparts, but have since conceptually diverged in many ways. The resulting network architectures are not well understood, and furthermore, we lack the quantitative t...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
In practical engineering, many systems are required to operate under different constraint conditions due to considerations of system security. Violating these constraints conditions during operation may lead to performance degradation. Additionally, ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Large language models (LLMs) roughly encode a sentence into a dense representation (a vector), which mixes up the semantic expression of all named entities within a sentence. So the decoding process is easily overwhelmed by sentence-specific informat...