AIMC Topic: Deep Learning

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DBA-ViNet: an effective deep learning framework for fruit disease detection and classification using explainable AI.

BMC plant biology
OBJECTIVE: The primary aim of this research is to develop an effective and robust model for identifying and classifying diseases in general fruits, particularly apples, guavas, mangoes, pomegranates, and oranges, utilizing computer vision techniques.

Classification of skin diseases with deep learning based approaches.

Scientific reports
Skin diseases are one of the most common health problems that affect people of all ages around the world and significantly reduce the quality of life of individuals. Diseases of eczema, seborrheic dermatitis and skin cancer need to be diagnosed and c...

Creating interpretable deep learning models to identify species using environmental DNA sequences.

Scientific reports
Monitoring species' presence in an ecosystem is crucial for conservation and understanding habitat diversity, but can be expensive and time consuming. As a result, ecologists have begun using the DNA that animals naturally leave behind in water or so...

A new low-rank adaptation method for brain structure and metastasis segmentation via decoupled principal weight direction and magnitude.

Scientific reports
Deep learning techniques have become pivotal in medical image segmentation, but their success often relies on large, manually annotated datasets, which are expensive and labor-intensive to obtain. Additionally, different segmentation tasks frequently...

Identifying Cocoa Flower Visitors: A Deep Learning Dataset.

Scientific data
Cocoa is a multi-billion-dollar industry but research on improving yields through pollination remains limited. New embedded hardware and AI-based data analysis is advancing information on cocoa flower visitors, their identity and implications for yie...

Sequence-based virtual screening using transformers.

Nature communications
Protein-ligand interactions play central roles in myriad biological processes and are of key importance in drug design. Deep learning approaches are becoming cost-effective alternatives to high-throughput experimental methods for ligand identificatio...

Multi-modal classification of retinal disease based on convolutional neural network.

Biomedical physics & engineering express
Retinal diseases such as age-related macular degeneration and diabetic retinopathy will lead to irreversible blindness without timely diagnosis and treatment. Optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) imag...

AMFormer-based framework for accident responsibility attribution: Interpretable analysis with traffic accident features.

PloS one
Accurately determining responsibility in traffic accidents is crucial for ensuring fairness in law enforcement and optimizing responsibility standards. Traditional methods predominantly rely on subjective judgments, such as eyewitness testimonies and...

Hyperparameter tuned deep learning-driven medical image analysis for intracranial hemorrhage detection.

PloS one
Intracranial haemorrhage (ICH) is a crucial medical emergency that entails prompt assessment and management. Compared to conventional clinical tests, the need for computerized medical assistance for properly recognizing brain haemorrhage from compute...

AI-driven skin cancer detection from smartphone images: A hybrid model using ViT, adaptive thresholding, black-hat transformation, and XGBoost.

PloS one
Skin cancer is a significant global public health issue, with millions of new cases identified each year. Recent breakthroughs in artificial intelligence, especially deep learning, possess considerable potential to enhance the accuracy and efficiency...