AIMC Topic: Deep Learning

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WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification.

Scientific reports Jul 2, 2025
Weed detection and classification using computer vision and deep learning techniques have emerged as crucial tools for precision agriculture, offering automated solutions for sustainable farming practices. This study presents a comprehensive approach...
Agriculture Deep Learning Plant Weeds Image Processing, Computer-Assisted Weed Control
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A deep learning model for early diagnosis of alzheimer's disease combined with 3D CNN and video Swin transformer.

Scientific reports Jul 2, 2025
Alzheimer's disease (AD) constitutes a neurodegenerative disorder predominantly observed in the geriatric population. If AD can be diagnosed early, both in terms of prevention and treatment, it is very beneficial to patients. Therefore, our team prop...
Humans Neural Networks, Computer Female Aged Male Deep Learning Imaging, Three-Dimensional Magnetic Resonance Imaging Alzheimer Disease Early Diagnosis
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TDNN achitecture with efficient channel attention and improved residual blocks for accurate speaker recognition.

Scientific reports Jul 2, 2025
In recent years, with the advancement of deep learning, Convolutional Neural Networks (CNNs) have been widely applied in speaker recognition, making CNN-based speaker embedding learning the predominant method for speaker verification. Time Delay Neur...
Deep Learning Humans Neural Networks, Computer Algorithms
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DASNet a dual branch multi level attention sheep counting network.

Scientific reports Jul 2, 2025
Grassland sheep counting is essential for both animal husbandry and ecological balance. Accurate population statistics help optimize livestock management and sustain grassland ecosystems. However, traditional counting methods are time-consuming and c...
Sheep Grassland Unmanned Aerial Devices Animal Husbandry Deep Learning Neural Networks, Computer Animals
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Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension.

Scientific reports Jul 2, 2025
To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its pote...
Humans Female Adult Radiomics Male Brain Injuries, Traumatic Intracranial Pressure Deep Learning Intracranial Hypertension Middle Aged ROC Curve Optic Nerve Hemodynamics Nomograms Decompressive Craniectomy
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A federated learning-based privacy-preserving image processing framework for brain tumor detection from CT scans.

Scientific reports Jul 2, 2025
The detection of brain tumors is crucial in medical imaging, because accurate and early diagnosis can have a positive effect on patients. Because traditional deep learning models store all their data together, they raise questions about privacy, comp...
Image Processing, Computer-Assisted Privacy Federated Learning Tomography, X-Ray Computed Brain Neoplasms Deep Learning Neural Networks, Computer Algorithms Humans
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Deep learning deciphers the related role of master regulators and G-quadruplexes in tissue specification.

Scientific reports Jul 2, 2025
G-quadruplexes (GQs) are non-canonical DNA structures encoded by G-flipons with potential roles in gene regulation and chromatin structure. Here, we explore the role of G-flipons in tissue specification. We present a deep learning-based framework for...
Genome, Human G-Quadruplexes Promoter Regions, Genetic DNA Gene Expression Regulation Organ Specificity Humans Deep Learning
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Key factors in predictive analysis of cardiovascular risks in public health.

Scientific reports Jul 2, 2025
This research emphasizes the role of analytics in evaluating the risk of disease (CVD) focusing on thorough data preparation and feature engineering for accurate predictions. We studied machine learning (ML) and learning (DL) models, such as Logistic...
Risk Factors Cardiovascular Diseases Risk Assessment Humans Machine Learning ROC Curve Public Health Logistic Models Deep Learning Heart Disease Risk Factors
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Advancing BCI with a transformer-based model for motor imagery classification.

Scientific reports Jul 2, 2025
Brain-computer interfaces (BCIs) harness electroencephalographic signals for direct neural control of devices, offering significant benefits for individuals with motor impairments. Traditional machine learning methods for EEG-based motor imagery (MI)...
Imagination Electroencephalography Brain-Computer Interfaces Humans Machine Learning Neural Networks, Computer Algorithms Deep Learning
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Ensemble methods and partially-supervised learning for accurate and robust automatic murine organ segmentation.

Scientific reports Jul 2, 2025
Delineation of multiple organs in murine µCT images is crucial for preclinical studies but requires manual volumetric segmentation, a tedious and time-consuming process prone to inter-observer variability. Automatic deep learning-based segmentation c...
Reproducibility of Results Animals Mice Deep Learning Supervised Machine Learning Imaging, Three-Dimensional X-Ray Microtomography Image Processing, Computer-Assisted
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