AIMC Topic: Deep Learning

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FCMI-YOLO: An efficient deep learning-based algorithm for real-time fire detection on edge devices.

PloS one
The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under...

GNN-RMNet: Leveraging graph neural networks and GPS analytics for driver behavior and route optimization in logistics.

PloS one
Logistics networks are becoming increasingly complex and rely more heavily on real-time vehicle data, necessitating intelligent systems to monitor driver behavior and identify route anomalies. Traditional techniques struggle to capture the dynamic sp...

Advancing smart communities with a deep learning framework for sustainable resource management.

PloS one
BACKGROUND: The rapid development of urban systems and rising requirements for sustainable development lift resource management issues in smart communities. A fundamental problem for contemporary communities involves effectively using energy and wate...

TRI-PLAN: A deep learning-based automated assessment framework for right heart assessment in transcatheter tricuspid valve replacement planning.

International journal of cardiology
BACKGROUND: Efficient and accurate preoperative assessment of the right-sided heart structural complex (RSHSc) is crucial for planning transcatheter tricuspid valve replacement (TTVR). However, current manual methods remain time-consuming and inconsi...

Pred5AOP: an efficient screening of food-derived antioxidant peptides based on deep learning, molecular docking, and experimental validation.

Food chemistry
Antioxidant peptides derived from dietary proteins positively impact human health due to their high activity and safety. In this study, a database of 76,343 peptides was constructed via in silico hydrolysis of 29 dietary proteins. A novel antioxidant...

Label-free chimeric antigen receptor T-cell expression analysis using neural networks and statistical distribution modeling.

Biochemical and biophysical research communications
Chimeric antigen receptor T (CAR-T)-cell therapy has emerged as a promising treatment for hematologic malignancies. Accurate monitoring of CAR expression levels is essential for optimizing therapeutic efficacy and ensuring patient safety. Conventiona...

Surgical augmented reality registration methods: A review from traditional to deep learning approaches.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Augmented Reality (AR) has gained significant interest within the research community in the past two decades. In surgery, AR overlays critical information directly onto the surgeon's visual field, thus enhancing situational awareness by providing nav...

DeepHybrid-CNN: A hybrid approach for pre-processing of skin cancer images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In the current technological era, digital imaging is ubiquitous, and it serves a crucial purpose in the realm of medical research. Skin cancer is one of the most common types of cancer, and its early diagnosis is essential to reduce the mortality rat...

Integrating Physics-Based Simulations with Data-Driven Deep Learning Represents a Robust Strategy for Developing Inhibitors Targeting the Main Protease.

Journal of chemical information and modeling
The coronavirus main protease, essential for viral replication, is a well-validated antiviral target. Here, we present Deep-CovBoost, a computational pipeline integrating deep learning with free energy perturbation (FEP) simulations to guide the stru...

Deep manifold learning reveals hidden developmental dynamics of a human embryo model.

Science advances
In this study, postimplantation human epiblast and amnion development are modeled using a stem cell-based embryoid system. A dataset of 3697 fluorescent images, along with tissue, cavity, and cell masks, is generated from experimental data. A computa...