AIMC Topic: Deep Learning

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LeFood-set: Baseline performance of predicting level of leftovers food dataset in a hospital using MT learning.

PloS one
Monitoring the remaining food in patients' trays is a routine activity in healthcare facilities as it provides valuable insights into the patients' dietary intake. However, estimating food leftovers through visual observation is time-consuming and bi...

HD-6mAPred: a hybrid deep learning approach for accurate prediction of N6-methyladenine sites in plant species.

PeerJ
BACKGROUND: N6-methyladenine (6mA) is an important DNA methylation modification that serves a crucial function in various biological activities. Accurate prediction of 6mA sites is essential for elucidating its biological function and underlying mech...

An efficient leukemia prediction method using machine learning and deep learning with selected features.

PloS one
Leukemia is a serious problem affecting both children and adults, leading to death if left untreated. Leukemia is a kind of blood cancer described by the rapid proliferation of abnormal blood cells. An early, trustworthy, and precise identification o...

Apple varieties, diseases, and distinguishing between fresh and rotten through deep learning approaches.

PloS one
Apples are one of the most productive fruits in the world, in addition to their nutritional and health advantages for humans. Even with the continuous development of AI in agriculture in general and apples in particular, automated systems continue to...

Investigating the Key Trends in Applying Artificial Intelligence to Health Technologies: A Scoping Review.

PloS one
BACKGROUND: The use of Artificial Intelligence (AI) is exponentially rising in the healthcare sector. This change influences various domains of early identification, diagnosis, and treatment of diseases.

Deep learning-based fine-grained assessment of aneurysm wall characteristics using 4D-CT angiography.

PeerJ
PURPOSE: This study proposes a novel deep learning-based approach for aneurysm wall characteristics, including thin-walled (TW) and hyperplastic-remodeling (HR) regions.

Integrating temporal convolutional networks with metaheuristic optimization for accurate software defect prediction.

PloS one
The increasing importance of deep learning in software development has greatly improved software quality by enabling the efficient identification of defects, a persistent challenge throughout the software development lifecycle. This study seeks to de...

A super resolution generative adversarial networks and partition-based adaptive filtering technique for detect and remove flickers in digital color images.

PloS one
Eliminating flickering from digital images captured by cameras equipped with a rolling shutter is of paramount importance in computer vision applications. The ripple effect observed in an individual image is a consequence of the non-synchronized expo...

Brain tumor classification using MRI images and deep learning techniques.

PloS one
Brain tumors pose a significant medical challenge, necessitating early detection and precise classification for effective treatment. This study aims to address this challenge by introducing an automated brain tumor classification system that utilizes...

Deep learning based semantic segmentation of leukemia effected white blood cell.

PloS one
Medical image segmentation has numerous applications in diagnosing different diseases. Various types of diseases are found in white blood and Red blood cells. This paper represents the segmentation of WBCs from blood smear images. It is a complex and...