IEEE transactions on neural networks and learning systems
Feb 28, 2025
Synaptic plasticity plays a critical role in the expression power of brain neural networks. Among diverse plasticity rules, synaptic scaling presents indispensable effects on homeostasis maintenance and synaptic strength regulation. In the current mo...
IEEE transactions on neural networks and learning systems
Feb 28, 2025
Generating virtual organ populations that capture sufficient variability while remaining plausible is essential to conduct in silico trials (ISTs) of medical devices. However, not all anatomical shapes of interest are always available for each indivi...
IEEE transactions on neural networks and learning systems
Feb 28, 2025
With the continuous development of deep learning (DL), the task of multimodal dialog emotion recognition (MDER) has recently received extensive research attention, which is also an essential branch of DL. The MDER aims to identify the emotional infor...
IEEE transactions on neural networks and learning systems
Feb 28, 2025
Human activity recognition (HAR) is a popular research field in computer vision that has already been widely studied. However, it is still an active research field since it plays an important role in many current and emerging real-world intelligent s...
In recent years, generating 3D human models from images has gained significant attention in 3D human reconstruction. However, deploying large neural network models in practical applications remains challenging, particularly on resource-constrained ed...
Robotic monocular pose estimation is an important part of neural monocular pose estimation-driven methods, which includes monocular simultaneous localization and mapping (SLAM) and single-view object pose estimation (OPE) driven by neural methods. Th...
Effective fruit identification and maturity detection are important for harvesting and managing tomatoes. Current deep learning detection algorithms typically demand significant computational resources and memory. Detecting severely stacked and obscu...
Accurate molecular property prediction is crucial for drug discovery and computational chemistry, facilitating the identification of promising compounds and accelerating therapeutic development. Traditional machine learning falters with high-dimensio...
This study introduces a novel deep learning approach aimed at accurately classifying Gallbladder Cancer (GBC) into benign, malignant, and normal categories using ultrasound images from the challenging GBC USG (GBCU) dataset. The proposed methodology ...
UNLABELLED: is a comparative analysis of algorithms for segmentation of three-dimensional OCT images of human skin using neural networks based on U-Net architecture when training the model on two-dimensional and three-dimensional data.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.