Academic Articles & Research Papers

Deep-Learning-Enhanced TopoStats for the Automated Quantification of DNA and Complex Biomolecular Structures.

A SAM2 and VLM-Based Automatic Radiological Reporting System for Pneumothorax Detection

Background/Objectives: Pneumothorax, caused by air accumulation in the pleural space, can lead to lung collapse and, if diagnosis is delayed, respiratory or cardiovascular deterioration. Most deep-learning studies on pneumothorax address cl...

LncRNA-Top: Controlled deep learning approaches for lncRNA gene regulatory relationship annotations across different platforms

Summary: By soaking microRNAs (miRNAs), long non-coding RNAs (lncRNAs) have the potential to regulate gene expression. Few methods have been created based on this mechanism to anticipate the lncRNA-gene relationship prediction. Hence, we pr...

TRANSFER LEARNING: INCEPTION-V3 BASED CUSTOM CLASSIFICATION APPROACH FOR FOOD IMAGES

Deep-learning approach has become more popular in the field of image processing. When it is concerned with health issues, there are lots of improvements in the applications of food image classification by deep learning methods. Transfer lea...

Quantum computing for finance: Overview and prospects

We discuss how quantum computation can be applied to financial problems, providing an overview of current approaches and potential prospects. We review quantum optimization algorithms , and expose how quantum annealers can be used to optimi...

Magnetic field reconstruction from proton radiography via physics-guided out-of-distribution filtering

Reconstructing multidimensional vector fields from path-integrated projection data is a fundamental challenge in high-energy-density physics, particularly when experimental sources exhibit spectral broadening and shot-to-shot jitter. We pre...

Adversarial Attacks on Deep-learning Models in Natural Language Processing

With the development of high computational devices, deep neural networks (DNNs), in recent years, have gained significant popularity in many Artificial Intelligence (AI) applications. However, previous efforts have shown that DNNs are vulne...

TRAMON: An automated traffic monitoring system for high density, mixed and lane-free traffic

This paper introduces a new visual dataset and framework to facilitate computer-vision-based traffic monitoring in high density, mixed and lane-free traffic (TRAMON). While there are advanced deep learning algorithms that can detect and tra...

Computer vision algorithms and hardware implementations: A survey

The field of computer vision is experiencing a great-leap-forward development today. This paper aims at providing a comprehensive survey of the recent progress on computer vision algorithms and their corresponding hardware implementations. ...

Deep-Learning based Melanoma Detection using Cloud Approach

The aim of computer vision techniquesand deep learning in the era of digitalization is to derive valuable insights from them and generate novel understanding. This makes it possible to employ imaging to quickly diagnose and treat a variety ...

SCM: A Searched Convolutional Metaformer for SAR Ship Classification

Ship classification technology using synthetic aperture radar (SAR) has become a research hotspot. Many deep-learning-based methods have been proposed with handcrafted models or using transplanted computer vision networks. However, most of ...

A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative -- th...

Deep learning based identification and tracking of railway bogie parts

The Train Rolling-Stock Examination (TRSE) is a safety examination process that physically examines the bogie parts of a moving train, typically at speeds over 30 km/h. Currently, this inspection process is done manually by railway personne...

Deep learning in nano-photonics: inverse design and beyond

Deep learning in the context of nano-photonics is mostly discussed in terms of its potential for inverse design of photonic devices or nano-structures. Many of the recent works on machine-learning inverse design are highly specific, and the...

Deep-learning–based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy

Abstract Background Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection. Objectives To estimate the diagnostic accu...

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 ...

Deep learning-based recognition and segmentation of intracranial aneurysms under small sample size

The manual identification and segmentation of intracranial aneurysms (IAs) involved in the 3D reconstruction procedure are labor-intensive and prone to human errors. To meet the demands for routine clinical management and large cohort studi...

Deep Learning for PET Image Reconstruction

This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for the reconstruction of images in positron emission tomography (PET). Deep learning can be used either directly or as a component of conventio...

Deep-learning-generated holography

We present a method for computer-generated holography based on deep learning. The inverse process of light propagation is regressed with a number of computationally generated speckle data sets. This method enables noniterative calculation o...

Deep Learning for Encrypted Traffic Classification: An Overview

Traffic classification has been studied for two decades and applied to a wide range of applications from QoS provisioning and billing in ISPs to security-related applications in firewalls and intrusion detection systems. Port-based, data pa...