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Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Rittik Chandra Das Turjy, Fahmid Al Farid, Fahmid Al Farid, Md. Hasan Imam Bijoy et al. • Frontiers in Artificial Intelligence (2026)

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1884567

Convolutional-de-convolutional neural networks for recognition of surgical workflow

Yu-wen Chen, Ju Zhang, Peng Wang, Zheng-yu Hu et al. • Frontiers in Computational Neuroscience (2022)

Computer-assisted surgery (CAS) has occupied an important position in modern surgery, further stimulating the progress of methodology and technology. In recent years, a large number of computer vision-based methods have been widely used in ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fncom.2022.998096

DEEP LEARNING-BASED DOOR AND WINDOW DETECTION FROM BUILDING FAÇADE

G. Sezen, M. Cakir, M. E. Atik, Z. Duran • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2022)

Detecting building façade elements is a crucial problem in computer vision for image interpretation. In Building Information Modeling (BIM) studies, the detection of building façade elements has an important role. BIM is a tool that allows ...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLIII-B4-2022-315-2022

DualSight: multi-stage instance segmentation framework for improved precision

Stephen Price, Kiran Judd, Kyle Tsaknopoulos, Rodica Neamtu et al. • Scientific Reports (2025)

Abstract Powder properties, particularly their morphology (which includes size, shape, surface roughness, etc.), play a critical role in the quality of cold spray additively manufactured materials. A change in feedstock powder morphology ca...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-09642-3

Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials

Haijie Ren, Weiqiang Wang, Wentao Tang, Rui Zhang • Physical Review Research (2024)

Topological defects play a key role in the structures and dynamics of liquid crystals and other ordered systems. There is a recent interest in studying defects in different biological systems with distinct textures. However, a robust method...

DOAJ Open Access (DOAJ) DOI: 10.1103/PhysRevResearch.6.013259

FIR-SDE: fast image restoration via mean-reverting stochastic differential equation

Xin Shi, Zhengchao Xu, Sunan Ge, Xueqing Zhao et al. • Complex & Intelligent Systems (2026)

Abstract In computer vision, zero-shot image restoration—a technique enabling degraded image restoration without large-scale paired training data—has emerged as a pivotal technique for scenarios where data is limited or paired training data...

DOAJ Open Access (DOAJ) DOI: 10.1007/s40747-025-02205-z

Computer Vision

Simon J. D. Prince • Cambridge University Press eBooks (2012)

This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the worl...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511996504

Boosting Neural Networks

Holger Schwenk, Yoshua Bengio • Neural Computation (2000)

Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, AdaBoost, has been applied with great success to several benchmark machine learning problems using mainly decision tr...

OPENALEX DOI: https://doi.org/10.1162/089976600300015178

Supervised Speech Separation Based on Deep Learning: An Overview

DeLiang Wang, Jitong Chen • IEEE/ACM Transactions on Audio Speech and Language Processing (2018)

Speech separation is the task of separating target speech from background interference. Traditionally, speech separation is studied as a signal processing problem. A more recent approach formulates speech separation as a supervised learning...

OPENALEX Open Access DOI: https://doi.org/10.1109/taslp.2018.2842159 PMC: 6586438

Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint

Michael Kloster, Andrea M. Burfeid-Castellanos, Daniel Langenkämper, Tim W. Nattkemper et al. • PLoS ONE (2023)

Diatoms represent one of the morphologically and taxonomically most diverse groups of microscopic eukaryotes. Light microscopy-based taxonomic identification and enumeration of frustules, the silica shells of these microalgae, is broadly us...

DOAJ Open Access (DOAJ)

Analysis of Customer Churn Classification for Sinarmas Syariah Lhokseumawe Insurance Services Using Deep Learning Tabnet and Explainable AI

Syarifah Muliana, Taufiq Taufiq, Munirul Ula • Journal of Applied Informatics and Computing (2026)

Customer churn is a major challenge in the insurance industry because it directly affects customer retention, business sustainability, and company profitability. Early identification of customers at risk of churn is therefore essential for ...

DOAJ Open Access (DOAJ) DOI: 10.30871/jaic.v10i3.12864

Compilation of training datasets for use of convolutional neural networks supporting automatic inspection processes in industry 4.0 based electronic manufacturing

A. I. M. Schwebig, A. I. M. Schwebig, R. Tutsch • Journal of Sensors and Sensor Systems (2020)

Ensuring the highest quality standards at competitive prices is one of the greatest challenges in the manufacture of electronic products. The identification of flaws has the uppermost priority in the field of automotive electronics, particu...

DOAJ Open Access (DOAJ) DOI: 10.5194/jsss-9-167-2020

Deep Learning for PET Image Reconstruction

Andrew J. Reader, Guillaume Corda-D’Incan, Abolfazl Mehranian, Casper O. da Costa-Luis et al. • IEEE Transactions on Radiation and Plasma Medical Sciences (2020)

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...

OPENALEX Open Access DOI: https://doi.org/10.1109/trpms.2020.3014786

Deep learning and computer vision will transform entomology

Toke T. Høye, Johanna Ärje, Kim Bjerge, Oskar Liset Pryds Hansen et al. • Proceedings of the National Academy of Sciences (2021)

ABSTRACT Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phe...

OPENALEX cc-by DOI: https://doi.org/10.1073/pnas.2002545117 PMC: 7812775

Deep Learning: An Update for Radiologists

Phillip M. Cheng, Emmanuel Montagnon, Rikiya Yamashita, Ian Pan et al. • Radiographics (2021)

Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the...

OPENALEX cc-by DOI: https://doi.org/10.1148/rg.2021200210

Deep learning: a statistical viewpoint

Peter L. Bartlett, Andrea Montanari A, Alexander Rakhlin • Acta Numerica (2021)

The remarkable practical success of deep learning has revealed some major surprises from a theoretical perspective. In particular, simple gradient methods easily find near-optimal solutions to non-convex optimization problems, and despite g...

OPENALEX cc-by DOI: https://doi.org/10.1017/s0962492921000027