Image and Object Detection Techniques

Neueste Paper

• ALINA: Advanced Line Identification and Notation Algorithm

  Mohammed Abdul Hafeez Khan, Parth Ganeriwala, Siddhartha Bhattacharyya, Natasha Neogi, Raja Muthalagu · 21. September 2026

  Labels are the cornerstone of supervised machine learning algorithms. Most visual recognition methods are fully supervised, using bounding boxes or pixel-wise segmentations for object localization. Traditional labeling methods, such as crowd-sourcing, are prohibitive due to cost, data privacy, amoun…

• Adaptive Dual-Constrained Line Aggregation for Cross-Paradigm Line Segment Detection

  Chenguang Liu, Chisheng Wang, Huilin Chen, Chuanhua Zhu, Qingquan Li · 11. September 2026

  Line segment detection has been studied for decades, yet existing methods are typically designed for different detection paradigms. Generic line segment detectors aim to recover all meaningful line segments in an image, whereas recent deep-learning-based approaches mainly target wireframe line segme…

• Soft-Argmax for the Projective Plane via the Veronese Embedding

  Benjamin El-Zein, Dominik Eckert, Paul Zech, Christopher Syben, Bernhard Geiger, Steffen Kappler, Sebastian Stober · 2. September 2026

  From horizon detection to fibre structures in X-ray imaging, many vision tasks recover lines via peak detection in Hough space $H=S^1\times\mathbb{R}$, the domain of orientation-offset pairs $(\theta,\rho)$. Differentiable pipelines extract coordinates via \emph{soft-argmax}, a probability-weighted …

• Advancing Utility Pole and Sign Detection Through Deep Learning

  Carl Dickinson, Gaetano Di Caterina · 5. August 2026

  Utility poles are an essential part of the infrastructure used to support power distribution systems and other critical public services. Their regular inspection is crucial to ensure the stability and safety of the electrical grid. A deep learning framework is presented for the automated detection, …

• ANGLE: Angular Neural Generative Learning via Engression

  Rajdeep Pathak, Archi Roy, Tanujit Chakraborty · 15. Juli 2026

  Circular data, representing angles or directions, are frequently encountered in computer vision, biology, geology, and meteorology. Traditional regression targets the conditional mean, which is often geometrically misleading for circular responses under multimodal, skewed, or asymmetric data structu…

• Lost in the Vibrations: Vision Language Models Fail the Dynamic Gauges Test

  Tairan Fu, Francisco Javier Santos-Martín, Javier Conde, Pedro Reviriego, Elena Merino-Gómez · 21. April 2026

  The digital transformation of industrial manufacturing increasingly relies on the ability of autonomous robots to interact with legacy infrastructure, particularly analog gauges. While Vision-Language Models (VLMs) have demonstrated potential in zero-shot instrument recognition, their deployment in …

• Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets

  Zixiong Yu, Guhan Chen, Jianfa Lai, Bohan Li, Songtao Tian · 27. März 2026

  Scaling factors in residual branches have emerged as a prevalent method for boosting neural network performance, especially in normalization-free architectures. While prior work has primarily examined scaling effects from an optimization perspective, this paper investigates their role in residual ar…

• Topologically Stable Hough Transform

  Stefan Huber, Kristóf Huszár, Michael Kerber, Martin Uray · 10. März 2026

  We propose an alternative formulation of the well-known Hough transform to detect lines in point clouds. Replacing the discretized voting scheme of the classical Hough transform by a continuous score function, its persistent features in the sense of persistent homology give a set of candidate lines.…

• Multi-instance robust fitting for non-classical geometric models

  Zongliang Zhang, Shuxiang Li, Xingwang Huang, Zongyue Wang · 6. Februar 2026

  Most existing robust fitting methods are designed for classical models, such as lines, circles, and planes. In contrast, fewer methods have been developed to robustly handle non-classical models, such as spiral curves, procedural character models, and free-form surfaces. Furthermore, existing method…

• Fast and Exact Least Absolute Deviations Line Fitting via Piecewise Affine Lower-Bounding

  Stefan Volz, Martin Storath, Andreas Weinmann · 25. Dezember 2025

  Least-absolute-deviations (LAD) line fitting is robust to outliers but computationally more involved than least squares regression. Although the literature includes linear and near-linear time algorithms for the LAD line fitting problem, these methods are difficult to implement and, to our knowledge…

• Error Slice Discovery via Manifold Compactness

  Han Yu, Hao Zou, Jiashuo Liu, Renzhe Xu, Yue He, Xingxuan Zhang, Peng Cui · 23. Dezember 2025

  Despite the great performance of deep learning models in many areas, they still make mistakes and underperform on certain subsets of data, i.e. error slices. Given a trained model, it is important to identify its semantically coherent error slices that are easy to interpret, which is referred to as …

• Vision-based module for accurately reading linear scales in a laboratory

  Parvesh Saini, Soumyadipta Maiti, Beena Rai · 18. Dezember 2025

  Capabilities and the number of vision-based models are increasing rapidly. And these vision models are now able to do more tasks like object detection, image classification, instance segmentation etc. with great accuracy. But models which can take accurate quantitative measurements form an image, as…

• Automatic Wire-Harness Color Sequence Detector

  Indiwara Nanayakkara, Dehan Jayawickrama, Mervyn Parakrama B. Ekanayake · 16. Dezember 2025

  Wire harness inspection process remains a labor-intensive process prone to errors in the modern Electronics Manufacturing Services (EMS) industry. This paper introduces a semiautomated machine vision system capable of verifying correct wire positioning, correctness of the connector polarity and corr…

• Depth Matching Method Based on ShapeDTW for Oil-Based Mud Imager

  Fengfeng Li, Zhou Feng, Hongliang Wu, Hao Zhang, Han Tian, Peng Liu, Lixin Yuan · 2. Dezember 2025

  In well logging operations using the oil-based mud (OBM) microresistivity imager, which employs an interleaved design with upper and lower pad sets, depth misalignment issues persist between the pad images even after velocity correction. This paper presents a depth matching method for borehole image…

• DialBench: Towards Accurate Reading Recognition of Pointer Meter using Large Foundation Models

  Futian Wang, Chaoliu Weng, Xiao Wang, Zhen Chen, Zhicheng Zhao, Jin Tang · 1. Dezember 2025

  The precise reading recognition of pointer meters plays a key role in smart power systems, but existing approaches remain fragile due to challenges like reflections, occlusions, dynamic viewing angles, and overly between thin pointers and scale markings. Up to now, this area still lacks large-scale …

• CVChess: A Deep Learning Framework for Converting Chessboard Images to Forsyth-Edwards Notation

  Luthira Abeykoon, Ved Patel, Gawthaman Senthilvelan, Darshan Kasundra · 17. November 2025

  Chess has experienced a large increase in viewership since the pandemic, driven largely by the accessibility of online learning platforms. However, no equivalent assistance exists for physical chess games, creating a divide between analog and digital chess experiences. This paper presents CVChess, a…