Academic Articles & Research Papers

Bi-Objective Portfolio Optimization Under ESG Volatility via a MOPSO-Deep Learning Algorithm

In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) informati...

Deployment optimization of laser chargers in self-organizing power transfer internet of things

Recently, the Internet of Things (IoT) has played an important role in many fields. Nevertheless, the fast and uneven energy consumption of IoT Devices (IoTDs) significantly limits the lifetime of IoT networks. One of the effective solution...

SPAF-SegNeXt: Prior-Guided Attention and Frequency-Spatial Hybrid Fusion for Multimodal Sugarcane Segmentation in Remote Sensing

Accurate monitoring of the spatial extent of sugarcane cultivation is critical for optimizing land-use efficiency and regulating the sugar industry. However, sugarcane cultivation areas are characterized by complex topography and fragmented...

A Review of Deep Learning Research

With the advent of big data, deep learning technology has become an important research direction in the field of machine learning, which has been widely applied in the image processing, natural language processing, speech recognition and on...

Regularization for Deep Learning: A Taxonomy

Regularization is one of the crucial ingredients of deep learning, yet the term regularization has various definitions, and regularization methods are often studied separately from each other. In our work we present a systematic, unifying t...

Deep learning for neuroimaging: a validation study

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neu...

Review of Deep Learning Algorithms and Architectures

Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars, predictive forecasting, and speech recognition. The pain...

Synthetic Data for Deep Learning

Deep Learning and Its Applications in Biomedicine

Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitat...

Deep reinforcement learning to enhance the energy-efficient performance of UAV-enabled F-RAN

Fog radio access network (F-RAN) is suitable for Internet of things applications of national important industries, such as pipeline network monitoring in wide area.However, the performance of the F-RAN based on the territorial fog access po...

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images

Abstract Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imba...

Review of Deep Learning for Language Modeling

[Purpose/Significance] Deep learning for language modeling is one of the major methods and advanced technologies to enhance language intelligence of machines at present, which has become an indispensable important technical means for automa...

Object Detection With Deep Learning: A Review

Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable...

Intelligent Distribution-Network Fault Handling via Cross-Modal Semantic Fusion and Knowledge-Graph Reasoning

Power distribution network fault handling imposes stringent requirements on both response timeliness and decision reliability. The high penetration of distributed renewable generation, the widespread deployment of power-electronic devices, ...

Precise Cruise Control for Fixed-Wing Aircraft Based on Proximal Policy Optimization with Nonlinear Attitude Constraints

In response to the issues of severe pitch oscillation and unstable roll attitude present in existing reinforcement learning-based aircraft cruise control methods during dynamic maneuvers, this paper proposes a precise control method for air...

Deep Learning

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...

A Machine Learning-Oriented Survey on Tiny Machine Learning

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...

Machine Learning for Engineers

This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering probl...

Machine learning in aerodynamic shape optimization

Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and pr...

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm

Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...