Treffer 1 - 20 von 787

1

Advancing software fault detection: A comparative study of neural network architectures.
Gunda, Sai Krishna
AIP Conference Proceedings. 2026, Vol. 3345 Issue 1, p1-13. 13p.

DEFECT tracking (Compute... RECEIVER operating chara... GENERALIZATION NEURAL computers COMPUTATIONAL complexity
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2

CAG-Net: A Novel Change Attention Guided Network for Substation Defect Detection.
Xiang, Dao ; Du, Xiaofei ; Liu, Zhaoyang
Mathematics (2227-7390). Jan2026, Vol. 14 Issue 1, p178. 19p.

DETECTION algorithms DEFECT tracking (Compute... ARTIFICIAL neural networ...
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3

Deterministic Record-and-Replay.
Quinn, Andrew ; Alvaro, Peter
Communications of the ACM. May2025, Vol. 68 Issue 5, p32-34. 3p.

DEFECT tracking (Compute... COMPUTER programming COMPUTER debugging softw... INTERNET servers CLOUD computing GRAPHICS processing unit...
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4

Deep multi-metrics learning for mobile app defect prediction using code and process metrics.
Abdu, Ahmed ; Abdo, Hakim A. ; Ullah, Inam ; et al.
Scientific Reports. 11/4/2025, Vol. 15 Issue 1, p1-21. 21p.

ANDROID (Operating syste... MOBILE apps DEFECT tracking (Compute... SOFTWARE measurement DEEP learning MODEL validation
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5

Defect Prediction Tool for Object-Oriented Software.
Alsarraj, Rasha Gh.
Iraqi Journal of Science. 2025, Vol. 69 Issue 10, p4490-4501. 12p.

COMPUTER software qualit... DEFECT tracking (Compute... QUALITY assurance OBJECT-oriented programm... SOFTWARE measurement
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6

Prioritization Method for Crowdsourced Test Report by Integrating Text and Image Information.
Tu, Huijie ; Yao, Xiangjuan ; Gong, Dunwei ; et al.
Journal of Software: Evolution & Process. Sep2025, Vol. 37 Issue 9, p1-15. 15p.

CROWDSOURCING DEFECT tracking (Compute... DATA analysis
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7

CPDD: A Cross-Scenario Photovoltaic Defect Detector Based on Fine-Grained Feature Autoencoding and Pseudo-Box Contrastive Learning.
Wang, Zhaoyang ; Chen, Haiyong ; Cao, Zhen
IEEE Transactions on Semiconductor Manufacturing. Aug2025, Vol. 38 Issue 3, p612-623. 12p.

PHOTOVOLTAIC power gener... DEFECT tracking (Compute... MACHINE learning VISUAL perception TECHNOLOGICAL innovation...
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8

Focusing on effective approach by enhancing accuracy by using agile methodology.
Kannan, G. ; Rajakumari, K.
AIP Conference Proceedings; 2026, Vol. 3345 Issue 1, p1-5, 5p

AGILE software developme... PROJECT management DEFECT tracking (Compute... SOFTWARE engineering SOFTWARE productivity
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9

An exploration of adaptive ensemble approaches in software fault detection: Balancing accuracy and robustness.
Gunda, Sai Krishna
AIP Conference Proceedings; 2026, Vol. 3345 Issue 1, p1-15, 15p

ENSEMBLE learning MACHINE learning DATA transformations (St... DEFECT tracking (Compute... ROBUST statistics STATISTICAL accuracy
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10

An explainable AI-based interpreter for deep-dual-wave based Unet framework with a cross-attention layer-based dental caries segmentation and classification.
Aelgani, Vivekanand ; Singh, Akansha ; Narayana, V. A.
Network Modeling & Analysis in Health Informatics & Bioinformatics; 3/7/2026, Vol. 15 Issue 1, p1-21, 21p

DEFECT tracking (Compute...
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11

Adaptive Ensemble Learning for Software Defect Prediction with Imbalanced Data.
Mehta, Ashu
International Journal of Performability Engineering. Mar2026, Vol. 22 Issue 3, p167-177. 11p.

Ensemble learning Adaptive sampling (Stati... Machine learning Defect tracking (Compute...
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12

Software Defect Prediction Based on Multi-Hypergraph Adaptive Learning and Ensemble Learning.
Liu, Weiguang ; Ren, Junyan ; Zhang, Wenning
IAENG International Journal of Computer Science. Mar2026, Vol. 53 Issue 3, p992-1006. 15p.

Ensemble learning Graph neural networks Machine learning Defect tracking (Compute... Mathematical optimizatio...
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13

Deep learning-based real-time monitoring of electron beam powder bed fusion (EB-PBF) via electron emission.
Gbadamosi-Adeniyi, Temilola ; Ferguson, Scott ; Horn, Tim
Journal of Intelligent Manufacturing; Mar2026, Vol. 37 Issue 3, p1297-1325, 29p

DEEP learning ELECTRON emission CONVOLUTIONAL neural net... AUTOENCODERS DEFECT tracking (Compute... REAL-time computing
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14

Towards label-free defect detection in additive manufacturing via dual-classifier semi-supervised learning for vision-language models.
Wang, Kang ; Liu, Lanqing ; Xu, Cheng ; et al.
Journal of Intelligent Manufacturing; Mar2026, Vol. 37 Issue 3, p1163-1178, 16p

QUALITY control THREE-dimensional printi... SUPERVISED learning DEFECT tracking (Compute... MACHINE learning
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15

Tile-DCGAN: a tile defect image generation method.
Wang, Xiaoyu ; Wu, Meishun ; Yang, Yong ; et al.
Signal, Image & Video Processing; Mar2026, Vol. 20 Issue 3, p1-11, 11p

GENERATIVE adversarial n... DATA augmentation DEEP learning QUALITY assurance CERAMIC material manufac... PROBABILISTIC generative...
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16

基于CT-ST半监督模型的城市地下管道缺陷语义 分割研究. (Chinese)
潘禹欣 ; 李波 ; 田淙文 ; et al.
Journal of South-Central Minzu University (Natural Science Edition); Mar2026, Vol. 45 Issue 2, p221-230, 10p

UNDERGROUND pipelines IMAGE segmentation MACHINE learning DEFECT tracking (Compute... SUPERVISED learning COMPUTER vision
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17

IoT Sensors in a Wireless Environment for Healthcare Monitoring: A Framework for Fault Detection.
Mulani, Altaf O. ; Liyakat, Kazi Kutubuddin Sayyad ; Warade, Nilima S. ; et al.
Journal of Pharmacology & Pharmacotherapeutics; Mar2026, Vol. 17 Issue 1, p94-100, 7p

INTERNET of things FAULT diagnosis PATIENT monitoring DEFECT tracking (Compute... STATISTICAL accuracy WIRELESS sensor nodes
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18

A robust LSTM-based defect identification methodology for imbalanced data of solder paste inspection.
Chiang, Tzu-An ; Che, Zhen-Hua ; Chen, Wei-Chien
International Journal of Advanced Manufacturing Technology; Feb2026, Vol. 142 Issue 11/12, p6471-6481, 11p

LONG short-term memory PRINCIPAL components ana... DEFECT tracking (Compute... DEEP learning DATA scrubbing DATA quality
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19

Large Language Model-guided Data Augmentation for You Only Look Once Version 8-based Printed Circuit Board Defect Detection: Novel Human--AI Codesign Approach.
Lee, Wei-Hong ; Chen, Chih-Cheng ; Jiang, Jin
Sensors & Materials; 2026, Vol. 38 Issue 2, Part 3, p935-952, 18p

DATA augmentation AUTOMATIC optical inspec... DEEP learning OBJECT recognition (Comp... DEFECT tracking (Compute... LANGUAGE models
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20

DAG-Guided Active Fuzzing: A Deterministic Approach to Detecting Race Conditions in Distributed Cloud Systems.
Zhao, Hongyi ; Li, Zhen ; Wu, Yueming ; et al.
Applied Sciences (2076-3417); Feb2026, Vol. 16 Issue 4, p2061, 19p

CLOUD computing security... SCHEDULING PENETRATION testing (Com... CLOUD computing DEFECT tracking (Compute...
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