ADHD/ADD

Aligning Small Datasets Using Domain Adversarial Learning: Applications in Automated in Vivo Oral Cancer Diagnosis.

Deep learning approaches for medical image analysis are limited by small data set size due to factors such as patient privacy and difficulties in obtaining expert labelling for each image. In medical imaging system development pipelines, phases for system development and classification algorithms often overlap with data collection, creating small disjoint data sets collected at numerous locations ...

STC-NLSTMNet: An Improved Human Activity Recognition Method Using Convolutional Neural Network with NLSTM from WiFi CSI.

Human activity recognition (HAR) has emerged as a significant area of research due to its numerous possible applications, including ambient assisted living, healthcare, abnormal behaviour detection, etc. Recently, HAR using WiFi channel state information (CSI) has become a predominant and unique approach in indoor environments compared to others (i.e., sensor and vision) due to its privacy-preserv...

Deep Learning-Based ADHD and ADHD-RISK Classification Technology through the Recognition of Children's Abnormal Behaviors during the Robot-Led ADHD Screening Game.

Although attention deficit hyperactivity disorder (ADHD) in children is rising worldwide, fewer studies have focused on screening than on the treatmen...

Deep-Learning-Based ADHD Classification Using Children's Skeleton Data Acquired through the ADHD Screening Game.

The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for ear...

An Embedded Framework for Fully Autonomous Object Manipulation in Robotic-Empowered Assisted Living.

Most of the humanoid social robots currently diffused are designed only for verbal and animated interactions with users, and despite being equipped wi...

Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal cancer care, despite extensive research on prognostic...

Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.

Reference-based cell-type annotation can significantly reduce time and effort in single-cell analysis by transferring labels from a previously-annotat...

Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach.

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder with a high degree of psychiatric and physical comorbidity, which complica...

Equipment Identification and Localization Method Based on Improved YOLOv5s Model for Production Line.

Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the u...

Simple add-on robotic traction device to the conventional endoscope: Will it be an efficient and safe tool for novice training on endoscopic submucosal dissection?

A Proactive Attack Detection for Heating, Ventilation, and Air Conditioning (HVAC) System Using Explainable Extreme Gradient Boosting Model (XGBoost).

The advent of Industry 4.0 has revolutionized the life enormously. There is a growing trend towards the Internet of Things (IoT), which has made life ...

Interpretability-Based Multimodal Convolutional Neural Networks for Skin Lesion Diagnosis.

Skin lesion diagnosis is a key step for skin cancer screening, which requires high accuracy and interpretability. Though many computer-aided methods, ...

A Method for Expanding the Training Set of White Blood Cell Images.

In medicine, the count of different types of white blood cells can be used as the basis for diagnosing certain diseases or evaluating the treatment ef...

Alpha-SGANet: A multi-attention-scale feature pyramid network combined with lightweight network based on Alpha-IoU loss.

The design of deep convolutional neural networks has resulted in significant advances and successes in the field of object detection. However, despite...

Explaining neural activity in human listeners with deep learning via natural language processing of narrative text.

Deep learning (DL) approaches may also inform the analysis of human brain activity. Here, a state-of-art DL tool for natural language processing, the ...

Deep Learning Based One-Class Detection System for Fake Faces Generated by GAN Network.

Recently, the dangers associated with face generation technology have been attracting much attention in image processing and forensic science. The cur...

Multi-environment robotic transitions through adaptive morphogenesis.

The current proliferation of mobile robots spans ecological monitoring, warehouse management and extreme environment exploration, to an individual con...

Get a grip: inward dactyl motions improve efficiency of sideways-walking gait for an amphibious crab-like robot.

Crabs are adept at traversing natural terrains that are challenging for mobile robots. Curved dactyls are a characteristic feature that engage terrain...

Temporal Coding in Spiking Neural Networks With Alpha Synaptic Function: Learning With Backpropagation.

The timing of individual neuronal spikes is essential for biological brains to make fast responses to sensory stimuli. However, conventional artificia...

3D face-model reconstruction from a single image: A feature aggregation approach using hierarchical transformer with weak supervision.

Convolutional Neural Networks (CNN) have gained popularity as the de-facto model for any computer vision task. However, CNN have drawbacks, i.e. they ...