AIMC Topic: Benchmarking

Clear Filters Showing 291 to 300 of 490 articles

TEM virus images: Benchmark dataset and deep learning classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To achieve the full potential of deep learning (DL) models, such as understanding the interplay between model (size), training strategy, and amount of training data, researchers and developers need access to new dedicated im...

Contrastive rendering with semi-supervised learning for ovary and follicle segmentation from 3D ultrasound.

Medical image analysis
Segmentation of ovary and follicles from 3D ultrasound (US) is the crucial technique of measurement tools for female infertility diagnosis. Since manual segmentation is time-consuming and operator-dependent, an accurate and fast segmentation method i...

Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics.

Sensors (Basel, Switzerland)
Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between ...

Benchmarking deep learning splice prediction tools using functional splice assays.

Human mutation
Hereditary disorders are frequently caused by genetic variants that affect pre-messenger RNA splicing. Though genetic variants in the canonical splice motifs are almost always disrupting splicing, the pathogenicity of variants in the noncanonical spl...

Benchmarking Audio Signal Representation Techniques for Classification with Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Audio signal classification finds various applications in detecting and monitoring health conditions in healthcare. Convolutional neural networks (CNN) have produced state-of-the-art results in image classification and are being increasingly used in ...

Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Advances in artificial intelligence-based methods have led to the development and publication of numerous systems for auto-segmentation in radiotherapy. These systems have the potential to decrease contour variability, which has been associated with ...

Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL.

IEEE journal of biomedical and health informatics
Electrocardiography (ECG) is a very common, non-invasive diagnostic procedure and its interpretation is increasingly supported by algorithms. The progress in the field of automatic ECG analysis has up to now been hampered by a lack of appropriate dat...