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Printed circuit board defect detection methods based on image processing, machine learning and deep learning: A survey
Q Ling, NAM Isa - IEEE access, 2023 - ieeexplore.ieee.org
Printed circuit boards (PCBs) are a nearly ubiquitous component of every kind of electronic
device. With the rapid development of integrated circuit and semiconductor technology, the …
device. With the rapid development of integrated circuit and semiconductor technology, the …
Next-generation deep learning based on simulators and synthetic data
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …
learn in a most artificial way: they require large quantities of labeled data to grasp even …
Group-wise correlation stereo network
Stereo matching estimates the disparity between a rectified image pair, which is of great
importance to depth sensing, autonomous driving, and other related tasks. Previous works …
importance to depth sensing, autonomous driving, and other related tasks. Previous works …
Monocular human pose estimation: A survey of deep learning-based methods
Vision-based monocular human pose estimation, as one of the most fundamental and
challenging problems in computer vision, aims to obtain posture of the human body from …
challenging problems in computer vision, aims to obtain posture of the human body from …
Human action recognition and prediction: A survey
Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …
have been moving from inferring the present state to predicting the future state. Vision-based …
Deep learning tools for the measurement of animal behavior in neuroscience
Highlights•Deep neural networks are shattering performance benchmarks in computer
vision for various tasks.•Using modern deep learning approaches (DNNs) in the lab is a …
vision for various tasks.•Using modern deep learning approaches (DNNs) in the lab is a …
Learning from simulated and unsupervised images through adversarial training
With recent progress in graphics, it has become more tractable to train models on synthetic
images, potentially avoiding the need for expensive annotations. However, learning from …
images, potentially avoiding the need for expensive annotations. However, learning from …
Motsynth: How can synthetic data help pedestrian detection and tracking?
Deep learning-based methods for video pedestrian detection and tracking require large
volumes of training data to achieve good performance. However, data acquisition in …
volumes of training data to achieve good performance. However, data acquisition in …
On-demand monitoring of construction projects through a game-like hybrid application of BIM and machine learning
While unavoidable, inspections, progress monitoring, and comparing as-planned with as-
built conditions in construction projects do not readily add tangible intrinsic value to the end …
built conditions in construction projects do not readily add tangible intrinsic value to the end …
Playing for data: Ground truth from computer games
Recent progress in computer vision has been driven by high-capacity models trained on
large datasets. Unfortunately, creating large datasets with pixel-level labels has been …
large datasets. Unfortunately, creating large datasets with pixel-level labels has been …