AI Medical Compendium Journal:
Neural networks : the official journal of the International Neural Network Society

Showing 71 to 80 of 2842 articles

DRTN: Dual Relation Transformer Network with feature erasure and contrastive learning for multi-label image classification.

Neural networks : the official journal of the International Neural Network Society
The objective of multi-label image classification (MLIC) task is to simultaneously identify multiple objects present in an image. Several researchers directly flatten 2D feature maps into 1D grid feature sequences, and utilize Transformer encoder to ...

Continual learning of conjugated visual representations through higher-order motion flows.

Neural networks : the official journal of the International Neural Network Society
Learning with neural networks from a continuous stream of visual information presents several challenges due to the non-i.i.d. nature of the data. However, it also offers novel opportunities to develop representations that are consistent with the inf...

PrivCore: Multiplication-activation co-reduction for efficient private inference.

Neural networks : the official journal of the International Neural Network Society
The marriage of deep neural network (DNN) and secure 2-party computation (2PC) enables private inference (PI) on the encrypted client-side data and server-side models with both privacy and accuracy guarantees, coming at the cost of orders of magnitud...

DuPt: Rehearsal-based continual learning with dual prompts.

Neural networks : the official journal of the International Neural Network Society
The rehearsal-based continual learning methods usually involve reviewing a small number of representative samples to enable the network to learn new contents while retaining old knowledge. However, existing works overlook two crucial factors: (1) Whi...

RISE-Editing: Rotation-invariant neural point fields with interactive segmentation for fine-grained and efficient editing.

Neural networks : the official journal of the International Neural Network Society
Neural Radiance Fields (NeRF) have shown great potential for synthesizing novel views. Currently, despite the existence of some initial controllable and editable NeRF methods, they remain limited in terms of efficient and fine-grained editing capabil...

Unambiguous granularity distillation for asymmetric image retrieval.

Neural networks : the official journal of the International Neural Network Society
Previous asymmetric image retrieval methods based on knowledge distillation have primarily focused on aligning the global features of two networks to transfer global semantic information from the gallery network to the query network. However, these m...

Augmenting sparse behavior data for user identity linkage with self-generated by model and mixup-generated samples.

Neural networks : the official journal of the International Neural Network Society
The user identity linkage task aims to associate user accounts belonging to the same individual by utilizing user data. This task is relevant in domains such as recommendation systems, where user-generated content (i.e., behavioral data) serves as th...

Episodic Memory-Double Actor-Critic Twin Delayed Deep Deterministic Policy Gradient.

Neural networks : the official journal of the International Neural Network Society
Existing deep reinforcement learning (DRL) algorithms suffer from the problem of low sample efficiency. Episodic memory allows DRL algorithms to remember and use past experiences with high return, thereby improving sample efficiency. However, due to ...

Quantum federated learning with pole-angle quantum local training and trainable measurement.

Neural networks : the official journal of the International Neural Network Society
Recently, quantum federated learning (QFL) has received significant attention as an innovative paradigm. QFL has remarkable features by employing quantum neural networks (QNNs) instead of conventional neural networks owing to quantum supremacy. In or...

Anxiety disorder identification with biomarker detection through subspace-enhanced hypergraph neural network.

Neural networks : the official journal of the International Neural Network Society
In this study, we propose a subspace-enhanced hypergraph neural network (seHGNN) for classifying anxiety disorders (AD), which are prevalent mental illnesses that affect a significant portion of the global population. Our seHGNN model utilizes a lear...