Academic Articles & Research Papers

A Dual-Segmentation Framework for the Automatic Detection and Size Estimation of Shrimp

In shrimp farming, determining the physical traits of shrimp is vital for assessing their health and growth. One of the critical traits is their size, as it serves as a key indicator of growth rates, biomass, and effective feed management. ...

Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in ...

Deep learning: A philosophical introduction

Abstract Deep learning is currently the most prominent and widely successful method in artificial intelligence. Despite having played an active role in earlier artificial intelligence and neural network research, philosophers have been larg...

Review of deep learning for photoacoustic imaging

Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...

Computer‐aided diagnosis in the era of deep learning

Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then ...

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery

Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estim...

HRCTCov19-a high-resolution chest CT scan image dataset for COVID-19 diagnosis and differentiation

Abstract Introduction Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the ...

Behavioral Motivation and Influencing Factors of Graduate Students Using AIGC Tool: An Empirical Analysis Based on Questionnaire Survey

[Purpose/Significance] To explore in depth the acceptance and usage habits of AIGC tools by graduate students in the process of academic research, and to promote the positive attention and application of emerging technologies by graduate st...

A review of deep learning in image recognition

Deep learning has been the core topic in machine learning and convolutional neural network is one of the most prominent approaches. Convolutional neural network has won numerous competitions in recent years. It has outstanding results in im...

Advances in Deep Learning

Deep learning in analytical chemistry

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...

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...

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...

Automated deep bottleneck residual 82-layered architecture with Bayesian optimization for the classification of brain and common maternal fetal ultrasound planes

Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...

DVNDTA: a dual virtual node based heterogeneous interaction model for accurate prediction of drug-target affinity

Abstract Efficient prediction of drug-target affinity (DTA) is crucial for accelerating drug discovery. Recently, deep learning approaches leveraging 3D complexes have shown strong potential for drug-target affinity prediction. However, mos...

Deep learning applications in ophthalmology

PURPOSE OF REVIEW: To describe the emerging applications of deep learning in ophthalmology. RECENT FINDINGS: Recent studies have shown that various deep learning models are capable of detecting and diagnosing various diseases afflicting the...

The Application of Deep Learning in Cancer Prognosis Prediction

Deep learning has been applied to many areas in health care, including imaging diagnosis, digital pathology, prediction of hospital admission, drug design, classification of cancer and stromal cells, doctor assistance, etc. Cancer prognosis...

Plant Disease Detection and Classification by Deep Learning—A Review

Deep learning is a branch of artificial intelligence. In recent years, with the advantages of automatic learning and feature extraction, it has been widely concerned by academic and industrial circles. It has been widely used in image and v...