Academic Articles & Research Papers

Deep Learning for Population Genetic Inference

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep...

Machine learning and deep learning applications in microbiome research

The many microbial communities around us form interactive and dynamic ecosystems called microbiomes. Though concealed from the naked eye, microbiomes govern and influence macroscopic systems including human health, plant resilience, and bio...

Deep Learning for the Internet of Things

How can the advantages of deep learning be brought to the emerging world of embedded IoT devices? The authors discuss several core challenges in embedded and mobile deep learning, as well as recent solutions demonstrating the feasibility of...

Deep learning: Evolution and expansion

Beyond Laughter: How Culture Shapes the Meaning and Preference of Humor.

Takotsubo syndrome with left ventricular thrombus: Prevention of systemic thromboembolism.

Testing the Role of Temporal Attention in Speech: Pretarget Alpha Predicts Memory Encoding Rather Than Effects of Linguistic Focus.

Neural Measures of Human Decision-Making Track Evidence Accumulation in Learned Space.

Refinement of Nucleus Accumbens Neuronal Dynamics during Cocaine Self-Administration Training.

Distinct activity in prefrontal projections promotes temporal control of action.

Nanopore-based 18S rRNA metabarcoding reveals Hepatozoon lineages from ectoparasites.

"I Can't Fully Explain It, but Something Just Feels Off": A Qualitative Study of Danish Students' Bystander Perceptions of Sexual Violence Risk.

Neuro-Symbolic Speech Understanding in Aircraft Maintenance Metaverse

In the emerging world of metaverses, it is essential for speech communication systems to be aware of context to interact with virtual assets in the 3D world. This paper proposes the metaverse for aircraft maintenance training and education ...

Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization

Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative ...

Greedy Broad Learning System

In order to overcome the extremely time-consuming drawback of deep learning (DL), broad learning system (BLS) was proposed as an alternative method. This model is simple, fast, and easy to update. To ensure the fitting and generalization ab...

A System for the Detection of Polyphonic Sound on a University Campus Based on CapsNet-RNN

In recent decades, surveillance and home security systems based on video analysis have been proposed for the automatic detection of abnormal situations. Nevertheless, in several real applications, it may be easier to detect a given event fr...

A Self-Attention Feature Fusion Model for Rice Pest Detection

To address the problem that existing deep learning methods are not sufficiently accurate to detect rice pests with changeable shapes or similar appearances, a self-attention feature fusion model for rice pest detection (SAFFPest) was propos...

Comprehensive framework of machine learning and deep learning architectures with metaheuristic optimization for high-fidelity prediction of nanofluid specific heat capacity

Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...

Predicting Shield Machine Penetration Rate Using the CTCM-DELM Algorithm

The penetration rate (PR) is a critical indicator affecting the safety and cost of shield tunnel construction. However, due to the complexity of geological conditions and the nonlinear nature of tunneling parameters, traditional prediction ...

Transmission line fault detection and classification based on SA-MobileNetV3

Accurate fault detection and classification help to analyze fault causes and quickly restore faulty phases. Deep learning can automatically extract fault features and identify fault types from the original three-phase voltage and current si...