AIMC Topic: Deep Learning

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Integrating swin transfer with attention mechanism based hybrid deep learning driven automated human activity recognition for enhanced disability assistance.

Scientific reports
The challenge of providing independent living for elderly and disabled individuals is a critical societal concern. Accurate human activity recognition (HAR) is core to allow the development of context-aware applications that involve the identificatio...

A dual attention and cross layer fusion network with a hybrid CNN and transformer architecture for medical image segmentation.

Scientific reports
Medical image segmentation is a crucial technology for disease diagnosis and treatment planning. However, current approaches face challenges in capturing global semantic dependencies and integrating cross-layer features. While Convolutional Neural Ne...

Classification of cotton leaf disease using YOLOv8 based k-fold cross validation deep learning method for precision agriculture.

Scientific reports
Cotton production is a crucial agricultural industry, a raw material source for the textiles sector and a major source of livelihood for more than 30 million farmers globally. The yield and quality of cotton (Gossypium) are influenced by different ty...

A deep learning AI model for determining the relationship between X-Ray detectors and patient positioning in chest radiography.

PloS one
PURPOSE: The objective of this study was to create an artificial intelligence (AI) system capable of automatically detecting the positional relationship between an X-ray detector and the patient during anteroposterior chest radiography.

Computer Vision-Assisted Data Analysis for Correlative Electron Microscopy and Secondary Ion Mass Spectrometry Imaging.

Analytical chemistry
Correlative imaging is a powerful analytical approach in bioimaging, as it offers complementary information on the samples measured by different modalities. Particularly, correlative transmission electron microscopy (EM) and nanoscale secondary ion m...

A multi-task deep learning model based on transformer for simultaneously evaluating the TVB-N and TVC contents of chicken breasts using two different hyperspectral imaging.

Food chemistry
Accurate assessment of freshness is crucial for ensuring quality and safety in the chicken meat industry. This study developed a Multi-task Interleaved Group Transformer Model (MIGTM) integrating dual hyperspectral imaging (HSI) data to simultaneousl...

Deep learning approach for tooth numbering and restoration detection on pediatric periapical radiographs in mixed dentition.

Clinical oral investigations
OBJECTIVES: Accurate tooth numbering and restoration detection on periapical radiographs in mixed dentition are critical to the treatment planning process. They also improve the speed and accuracy of treatment processes by automating the early diagno...

Segmenting beyond the imaging data: creation of anatomically valid edentulous mandibular geometries for surgical planning using artificial intelligence.

Clinical oral investigations
BACKGROUND AND OBJECTIVES: Mandibular reconstruction following continuity resection due to tumor ablation or osteonecrosis remains a significant challenge in maxillofacial surgery. Virtual surgical planning (VSP) relies on accurate segmentation of th...

Mapping Context-Aware Phosphosite Regulation of Protein-Protein Interactions Using Deep Learning and Pan-Cancer Proteomics.

Journal of chemical information and modeling
Phosphorylation dynamically orchestrates the protein-protein interaction (PPI) network that governs cellular signaling, and its dysregulation frequently drives malignant transformation and neurodegeneration. We present PhosPPI-SEQ, an interpretable d...

GLA-Synergy: An Interpretable Global-Local Adaptive Framework for Drug Synergy Prediction in Cancer Treatment.

Journal of chemical information and modeling
Effective anticancer drug combinations are crucial for advancing cancer treatment, yet predicting drug synergy remains challenging due to the complexity of biological interactions. Existing methods struggle to integrate multimodal features and to mod...