AIMC Topic: Neural Networks, Computer

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Comparative analysis and investigation of ultrasonication on juice yield and bioactive compounds of kinnow fruit using RSM and ANN models.

Scientific reports
Ultrasonication (US) is a promising non-thermal technique widely applied in the food sector for improving the extraction process and preserving nutrients. Kinnow fruits have yields of 40-60% juice; the rest of the parts are discarded as waste. The st...

Forecasting the concentration of the components of the particulate matter in Poland using neural networks.

Environmental science and pollution research international
Air pollution is a significant global challenge with profound impacts on human health and the environment. Elevated concentrations of various air pollutants contribute to numerous premature deaths each year. In Europe, and particularly in Poland, air...

Optimizing deep learning models for glaucoma screening with vision transformers for resource efficiency and the pie augmentation method.

PloS one
Glaucoma is the leading cause of irreversible vision impairment, emphasizing the critical need for early detection. Typically, AI-based glaucoma screening relies on fundus imaging. To tackle the resource and time challenges in glaucoma screening with...

DT-Transformer: A Text-Tactile Fusion Network for Object Recognition.

IEEE transactions on haptics
Humans rely on multiple senses to understand their surroundings, and so do robots. Current research in haptic object classification focuses on visual-haptic methods, but faces limitations in performance and dataset size. Unlike images, text does not ...

Object Recognition Using Shape and Texture Tactile Information: A Fusion Network Based on Data Augmentation and Attention Mechanism.

IEEE transactions on haptics
Currently, most tactile-based object recognition algorithms focus on single shape or texture recognition. However, these single attribute-based recognition methods perform poorly when dealing with objects with similar shape or texture characteristics...

Estimating uncertainty from feed-forward network based sensing using quasi-linear approximation.

Neural networks : the official journal of the International Neural Network Society
A fundamental problem in neural network theory is the quantification of uncertainty as it propagates through these constructs. Such quantification is crucial as neural networks become integrated into broader engineered systems that render decisions b...

Smart waste management and air pollution forecasting: Harnessing Internet of things and fully Elman neural network.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
As the Internet of things (IoT) continues to transform modern technologies, innovative applications in waste management and air pollution monitoring are becoming critical for sustainable development. In this manuscript, a novel smart waste management...

Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study.

Journal of theoretical biology
Cholera, an acute diarrheal disease, is a serious concern in developing and underdeveloped areas. A qualitative understanding of cholera epidemics aims to foresee transmission patterns based on reported data and mechanistic models. The mechanistic mo...

Enhancing skin disease classification leveraging transformer-based deep learning architectures and explainable AI.

Computers in biology and medicine
Skin diseases affect over a third of the global population, yet their impact is often underestimated. Automating the classification of these diseases is essential for supporting timely and accurate diagnoses. This study leverages Vision Transformers,...

GANDALF: Generative ANsatz for DNA damage evALuation and Forecast. A neural network-based regression for estimating early DNA damage across micro-nano scales.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: This study aims to develop a comprehensive simulation framework to connect radiation effects from the microscopic to the nanoscopic scale.