AIMC Topic: Deep Learning

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Multi-View Self-Supervised Learning Enhances Automatic Sleep Staging From EEG Signals.

IEEE transactions on bio-medical engineering
Deep learning-based methods for automatic sleep staging offer an efficient and objective alternative to costly manual scoring. However, their reliance on extensive labeled datasets and the challenge of generalization to new subjects and datasets limi...

A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision.

IEEE transactions on visualization and computer graphics
Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision. This article presents a comprehensive survey of deep learning in sports performance, focusing on three main ...

Single-View 3D Hair Modeling With Clumping Optimization.

IEEE transactions on visualization and computer graphics
Deep learning advancements have enabled the generation of visually plausible hair geometry from a single image, but the results still do not meet the realism required for further applications (e.g., high quality hair rendering and simulation). One of...

Artificial Intelligence-Based Classification of Renal Oncocytic Neoplasms: Advancing From a 2-Class Model of Renal Oncocytoma and Low-Grade Oncocytic Tumor to a 3-Class Model Including Chromophobe Renal Cell Carcinoma.

Archives of pathology & laboratory medicine
CONTEXT.—: Distinguishing between renal oncocytic tumors, such as renal oncocytoma (RO), and a subset of tumors with overlapping characteristics, including the recently identified low-grade oncocytic tumor (LOT), can present a diagnostic challenge fo...

Deep learning-assisted self-cleaning cellulose colorimetric sensor array for monitoring black tea withering dynamics.

Food chemistry
The withering process is a critical stage in developing the aroma profile of black tea. In this study, we presented an eco-friendly cellulose film-based colorimetric sensor array (CSA) for detecting volatile organic compounds (VOCs) and assessing wit...

[Synthetic promoters: theory, design, and prospects].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Synthetic promoters are novel promoters artificially designed and do not exist in nature. They can initiate the expression of target genes with specific regulatory modes, offering advantages such as high expression efficiency, precise regulation, and...

Enhancing pathological myopia diagnosis: a bimodal artificial intelligence approach integrating fundus and optical coherence tomography imaging for precise atrophy, traction and neovascularisation grading.

The British journal of ophthalmology
BACKGROUND: Pathological myopia (PM) has emerged as a leading cause of global visual impairment, early detection and precise grading of PM are crucial for timely intervention. The atrophy, traction and neovascularisation (ATN) system is applied to de...

Enhanced detection of Argulus and epizootic ulcerative syndrome in fish aquaculture through an improved deep learning model.

Journal of aquatic animal health
OBJECTIVE: Fish disease in aquaculture is a major risk to food safety. The identification of infected fish and disease categories present in fish farms remains difficult to determine at an early stage. Detecting infected fish in time is an essential ...

Enhanced Detection, Using Deep Learning Technology, of Medial Meniscal Posterior Horn Ramp Lesions in Patients with ACL Injury.

The Journal of bone and joint surgery. American volume
BACKGROUND: Meniscal ramp lesions can impact knee stability, particularly when associated with anterior cruciate ligament (ACL) injuries. Although magnetic resonance imaging (MRI) is the primary diagnostic tool, its diagnostic accuracy remains subopt...

HBUED: An EEG dataset for emotion recognition.

Journal of affective disorders
Emotion recognition via electroencephalogram (EEG) data is crucial for improving human-computer interaction. In practice, researchers require a substantial quantity of EEG samples to train and validate models. However, existing EEG datasets typically...