AIMC Topic: Neural Networks, Computer

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Development of a method for estimating asari clam distribution by combining three-dimensional acoustic coring system and deep neural network.

Scientific reports
Developing non-contact, non-destructive monitoring methods for marine life is crucial for sustainable resource management. Recent monitoring technologies and machine learning analysis advancements have enhanced underwater image and acoustic data acqu...

Decoding viewer emotions in video ads.

Scientific reports
Understanding and predicting viewers' emotional responses to videos has emerged as a pivotal challenge due to its multifaceted applications in video indexing, summarization, personalized content recommendation, and effective advertisement design. A m...

NSSC: a neuro-symbolic AI system for enhancing accuracy of named entity recognition and linking from oncologic clinical notes.

Medical & biological engineering & computing
Accurate recognition and linking of oncologic entities in clinical notes is essential for extracting insights across cancer research, patient care, clinical decision-making, and treatment optimization. We present the Neuro-Symbolic System for Cancer ...

GradToken: Decoupling tokens with class-aware gradient for visual explanation of Transformer network.

Neural networks : the official journal of the International Neural Network Society
Transformer networks have been widely used in the fields of computer vision, natural language processing, graph-structured data analysis, etc. Subsequently, explanations of Transformer play a key role in helping humans understand and analyze its deci...

Toward high-quality pseudo masks from noisy or weak annotations for robust medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Deep learning networks excel in image segmentation with abundant accurately annotated training samples. However, in medical applications, acquiring large quantities of high-quality labeled images is prohibitively expensive. Thus, learning from imperf...

Offline reward shaping with scaling human preference feedback for deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Designing reward functions that fully align with human intent is often challenging. Preference-based Reinforcement Learning (PbRL) provides a framework where humans can select preferred segments through pairwise comparisons of behavior trajectory seg...

A survey on representation learning for multi-view data.

Neural networks : the official journal of the International Neural Network Society
Multi-view clustering has become a rapidly growing field in machine learning and data mining areas by combining useful information from different views for last decades. Although there have been some surveys based on multi-view clustering, most of th...

Zero-shot counting with a dual-stream neural network model.

Neuron
To understand a visual scene, observers need to both recognize objects and encode relational structure. For example, a scene comprising three apples requires the observer to encode concepts of "apple" and "three." In the primate brain, these function...

Enhancing eco-sensing in aquatic environments: Fish jumping behavior automatic recognition using YOLOv5.

Aquatic toxicology (Amsterdam, Netherlands)
Contemporary research on ichthyological behavior predominantly investigates underwater environments. However, the intricate nature of aquatic ecosystems often hampers subaqueous observations of fish behavior due to interference. Transitioning the obs...

High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model.

Journal of environmental management
Ambient carbon monoxide (CO) is a primary air pollutant that poses significant health risks and contributes to the formation of secondary atmospheric pollutants, such as ozone (O). This study aims to elucidate global CO pollution in relation to healt...