AIMC Topic: Humans

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Improving Performance of Breast Lesion Classification Using a ResNet50 Model Optimized with a Novel Attention Mechanism.

Tomography (Ann Arbor, Mich.)
Background: The accurate classification between malignant and benign breast lesions detected on mammograms is a crucial but difficult challenge for reducing false-positive recall rates and improving the efficacy of breast cancer screening. Objective:...

ConcentrateNet: Multi-Scale Object Detection Model for Advanced Driving Assistance System Using Real-Time Distant Region Locating Technique.

Sensors (Basel, Switzerland)
This paper proposes a deep learning based object detection method to locate a distant region in an image in real-time. It concentrates on distant objects from a vehicular front camcorder perspective, trying to solve one of the common problems in Adva...

Deep Learning Models for Classification of Dental Diseases Using Orthopantomography X-ray OPG Images.

Sensors (Basel, Switzerland)
The teeth are the most challenging material to work with in the human body. Existing methods for detecting teeth problems are characterised by low efficiency, the complexity of the experiential operation, and a higher level of user intervention. Olde...

Toward Mental Effort Measurement Using Electrodermal Activity Features.

Sensors (Basel, Switzerland)
The ability to monitor mental effort during a task using a wearable sensor may improve productivity for both work and study. The use of the electrodermal activity (EDA) signal for tracking mental effort is an emerging area of research. Through analys...

Parallel Frequency Function-Deep Neural Network for Efficient Approximation of Complex Broadband Signals.

Sensors (Basel, Switzerland)
In recent years, with the growing popularity of complex signal approximation via deep neural networks, people have begun to pay close attention to the spectral bias of neural networks-a problem that occurs when a neural network is used to fit broadba...

Early Prediction of Diabetes Using an Ensemble of Machine Learning Models.

International journal of environmental research and public health
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of significant complications, including cardiovascular disease, kidney failure, diabetic retinopathy, and neuropathy, among others, which contribute to an incr...

A voting-based ensemble feature network for semiconductor wafer defect classification.

Scientific reports
Semiconductor wafer defects severely affect product development. In order to reduce the occurrence of defects, it is necessary to identify why they occur, and it can be inferred by analyzing the patterns of defects. Automatic defect classification (A...

Improving breast cancer diagnostics with deep learning for MRI.

Science translational medicine
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity in detecting breast cancer but often leads to unnecessary biopsies and patient workup. We used a deep learning (DL) system to improve the overall accuracy of breast...

Application of Big Data Technology and Visual Neural Network in Emotional Expression Analysis of Oil Painting Theme Creation in Public Environment.

Journal of environmental and public health
With the progress of science and technology and the arrival of the big data era, people increasingly rely on computers to deal with daily life and related affairs. In recent years, machine learning has become more and more popular and has achieved go...

Early Diagnosis of Tuberculosis Using Deep Learning Approach for IOT Based Healthcare Applications.

Computational intelligence and neuroscience
In the modern world, Tuberculosis (TB) is regarded as a serious health issue with a high rate of mortality. TB can be cured completely by early diagnosis. For achieving this, one tool utilized is CXR (Chest X-rays) which is used to screen active TB. ...