AIMC Topic: Neural Networks, Computer

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HEp-2 image classification using a multi-class and multiple-binary classifier.

Medical & biological engineering & computing
In medicine, identifying the indirect immunofluorescence of human epithelial type 2 (HEp-2) cells plays a decisive role in the diagnosis of autoimmune diseases. The manual interpretation of Hep-2 cell images may lead to some limitations, such as subj...

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data.

Journal of chemical information and modeling
Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consumin...

Imaging Orientation of a Single Molecular Hierarchical Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency Generation Microscopy and Neural Network.

The journal of physical chemistry. B
In this work, we determined the tilt angles of molecular units in hierarchical self-assembled materials on a single-sheet level, which were not available previously. This was achieved by developing a fast line-scanning vibrational sum frequency gener...

Real-Time and Efficient Multi-Scale Traffic Sign Detection Method for Driverless Cars.

Sensors (Basel, Switzerland)
Traffic signs detection and recognition is an essential and challenging task for driverless cars. However, the detection of traffic signs in most scenarios belongs to small target detection, and most existing object detection methods show poor perfor...

FASTNN: A Deep Learning Approach for Traffic Flow Prediction Considering Spatiotemporal Features.

Sensors (Basel, Switzerland)
Traffic flow forecasting is a critical input to intelligent transportation systems. Accurate traffic flow forecasting can provide an effective reference for implementing traffic management strategies, developing travel route planning, and public tran...

Classification of Skin Cancer Lesions Using Explainable Deep Learning.

Sensors (Basel, Switzerland)
Skin cancer is among the most prevalent and life-threatening forms of cancer that occur worldwide. Traditional methods of skin cancer detection need an in-depth physical examination by a medical professional, which is time-consuming in some cases. Re...

Towards Robustifying Image Classifiers against the Perils of Adversarial Attacks on Artificial Intelligence Systems.

Sensors (Basel, Switzerland)
Adversarial machine learning (AML) is a class of data manipulation techniques that cause alterations in the behavior of artificial intelligence (AI) systems while going unnoticed by humans. These alterations can cause serious vulnerabilities to missi...

Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM.

Sensors (Basel, Switzerland)
Multistep power consumption forecasting is smart grid electricity management's most decisive problem. Moreover, it is vital to develop operational strategies for electricity management systems in smart cities for commercial and residential users. How...

Vibro-Acoustic Distributed Sensing for Large-Scale Data-Driven Leak Detection on Urban Distribution Mains.

Sensors (Basel, Switzerland)
Non-surfacing leaks constitute the dominant source of water losses for utilities worldwide. This paper presents advanced data-driven analysis methods for leak monitoring using commercial field-deployable semi-permanent vibro-acoustic sensors, evaluat...

Characterization of Biocomposites and Glass Fiber Epoxy Composites Based on Acoustic Emission Signals, Deep Feature Extraction, and Machine Learning.

Sensors (Basel, Switzerland)
This study presents the results of acoustic emission (AE) measurements and characterization in the loading of biocomposites at room and low temperatures that can be observed in the aviation industry. The fiber optic sensors (FOS) that can outperform ...