AIMC Topic: Deep Learning

Clear Filters Showing 5121 to 5130 of 28423 articles

Deep Incomplete Multi-view Clustering via Multi-level Imputation and Contrastive Alignment.

Neural networks : the official journal of the International Neural Network Society
Deep incomplete multi-view clustering (DIMVC) aims to enhance clustering performance by capturing consistent information from incomplete multiple views using deep models. Most existing DIMVC methods typically employ imputation-based strategies to han...

Cardiac motion correction with a deep learning network for perfusion defect assessment in single-photon emission computed tomography myocardial perfusion imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: In myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT), ungated studies are used for evaluation of perfusion defects despite motion blur. We investigate the potential benefit of motion correction usi...

FT-FEDTL: A fine-tuned feature-extracted deep transfer learning model for multi-class microwave-based brain tumor classification.

Computers in biology and medicine
The microwave brain imaging (MBI) system is an emerging technology used to detect brain tumors in their early stages. Multi-class microwave-based brain tumor (MBT) identification and classification are crucial due to the tumor's patterns and shape. M...

AI derived ECG global longitudinal strain compared to echocardiographic measurements.

Scientific reports
Left ventricular (LV) global longitudinal strain (LVGLS) is versatile; however, it is difficult to obtain. We evaluated the potential of an artificial intelligence (AI)-generated electrocardiography score for LVGLS estimation (ECG-GLS score) to diagn...

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...

A deep learning approach for ovarian cancer detection and classification based on fuzzy deep learning.

Scientific reports
Different oncologists make their own decisions about the detection and classification of the type of ovarian cancer from histopathological whole slide images. However, it is necessary to have an automated system that is more accurate and standardized...

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...

Enhancing MRI brain tumor classification: A comprehensive approach integrating real-life scenario simulation and augmentation techniques.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Brain cancer poses a significant global health challenge, with mortality rates showing a concerning surge over recent decades. The incidence of brain cancer-related mortality has risen from 140,000 to 250,000, accompanied by a doubling in new diagnos...

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...