Concept
Edge detection
Related publications (454)
Silicon CMOS and InGaAs(P)/InP SPADs for NIR/SWIR detection
Applications demanding imaging at low-light conditions at near-infrared (NIR) and short-wave infrared (SWIR) wavelengths, such as quantum information science, biophotonics, space imaging, and light detection and ranging (LiDAR), have accelerated the develo ...
EPFL2024Euclid: Improving the efficiency of weak lensing shear bias calibration
Frédéric Courbin, Georges Meylan, Malte Tewes, Yi Wang, Richard Massey, Marcello Farina
To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and ...
Edp Sciences S A2024Reducing Annotation Efforts in Electricity Theft Detection Through Optimal Sample Selection
Supervised machine learning models are receiving increasing attention in electricity theft detection due to their high detection accuracy. However, their performance depends on a massive amount of labeled training data, which comes from time-consuming and ...
Piscataway2024Subsurface fluorescence time-of-flight imaging using a large-format single-photon avalanche diode sensor for tumor depth assessment
Edoardo Charbon, Claudio Bruschini, Arin Can Ülkü, Yichen Feng
Significance: Fluorescence guidance is used clinically by surgeons to visualize anatomical and/or physiological phenomena in the surgical field that are difficult or impossible to detect by the naked eye. Such phenomena include tissue perfusion or molecula ...
Spie-Soc Photo-Optical Instrumentation Engineers2024Visual complexity of urban streetscapes: human vs computer vision
Understanding visual complexity of urban environments may improve urban design strategies and limit visual pollution due to advertising, road signage, telecommunication systems and machinery. This paper aims at quantifying visual complexity specifically in ...
New York2024DiGress: Discrete Denoising diffusion for graph generation
Pascal Frossard, Volkan Cevher, Igor Krawczuk, Bohan Wang, Clément Arthur Yvon Vignac
This work introduces DiGress, a discrete denoising diffusion model for generating graphs with categorical node and edge attributes. Our model utilizes a discrete diffusion process that progressively edits graphs with noise, through the process of adding or ...
2023Rigidity-Aware Detection for 6D Object Pose Estimation
Mathieu Salzmann, Yinlin Hu, Jingyu Li, Rui Song
Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...
Los Alamitos2023CLIP the Gap: A Single Domain Generalization Approach for Object Detection
Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit
Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain. While this has been well studied for image classification, the literature on SDG object detection remai ...
Los Alamitos2023Improving Few-Shot Object Detection with Object Part Proposals
Devis Tuia, Marc Conrad Russwurm, Arthur Chevalley
Few-Shot Object Detection (FSOD) allows fast adaptation of an object detection model to new classes of objects using few examples per class. This has many applications, in particular in satellite and aerial observation, as it allows learning from experts w ...
The Institute of Electrical and Electronics Engineers, Inc2023Learning Transformations To Reduce the Geometric Shift in Object Detection
Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit
The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...
Los Alamitos2023