ADHD/ADD

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, especially deep learning methods, have made remarkable achievements in skin lesion diagnosis, their generalization and interpretability are still a challenge. To solve this issue, we propose an interpretability-based multimodal convolutional neural n...

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 effects of diseases. The recognition and counting of white blood cells have important clinical significance. But the effect of recognition based on machine learning is affected by the size of the training set. At present, researchers mainly rely on ima...

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 ...

Ensemble classification combining ResNet and handcrafted features with three-steps training.

This work presents an ECG classifier for variable leads as a contribution to the Computing in Cardiology Challenge/CinC Challenge 2021. It aims to int...

Toward Mental Effort Measurement Using Electrodermal Activity Features.

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 electroder...

Computational Modeling of Structural Synaptic Plasticity in Echo State Networks.

Most existing studies on computational modeling of neural plasticity have focused on synaptic plasticity. However, regulation of the internal weights ...

Learning From Synthetic CT Images via Test-Time Training for Liver Tumor Segmentation.

Automatic liver tumor segmentation could offer assistance to radiologists in liver tumor diagnosis, and its performance has been significantly improve...

Accurate image-based identification of macroinvertebrate specimens using deep learning-How much training data is needed?

Image-based methods for species identification offer cost-efficient solutions for biomonitoring. This is particularly relevant for invertebrate studie...

A Neural Network Model for Color Element Data Analysis for Urban Spatial Environment.

In this paper, a CNN model for color element data analysis of the urban spatial environment is constructed through an in-depth study of color element ...

Biomedical Relation Extraction With Knowledge Graph-Based Recommendations.

Biomedical Relation Extraction (RE) systems identify and classify relations between biomedical entities to enhance our knowledge of biological and med...

A privacy preservation framework for feedforward-designed convolutional neural networks.

A feedforward-designed convolutional neural network (FF-CNN) is an interpretable neural network with low training complexity. Unlike a neural network ...

Decision-Making Application of the Cloud-Fog Hybrid Model Based on the Improved Convolutional Neural Network in Financial Services in Smart Medical Care.

In order to alleviate the "difficulty in seeing a doctor" for the masses, continuously optimize the service process, and explore new financial service...

Value-free random exploration is linked to impulsivity.

Deciding whether to forgo a good choice in favour of exploring a potentially more rewarding alternative is one of the most challenging arbitrations bo...

Novel Coronavirus and Common Pneumonia Detection from CT Scans Using Deep Learning-Based Extracted Features.

COVID-19 which was announced as a pandemic on 11 March 2020, is still infecting millions to date as the vaccines that have been developed do not preve...