25 papers · ranked by Valyu relevance
Shaikh, Humera, Jashanpreet, Kaur
—This paper presents a comprehensive survey of computational imaging (CI) techniques and their transformative impact on computer vision (CV) applications. Conventional imaging methods often fail to deliver high-fidelity visual data in challenging conditions, such as low light, motion blur, or high dynamic range scenes…
Yassine Himeur, Iraklis Varlamis, Hamza Kheddar, Abbes Amira + 4 more
'Shadi Atalla' 'Yashbir Singh' 'Fayçal Bensaali' 'Wathiq Mansoor'] Abstract—Computer Vision (CV) is playing a significant role in transforming society by utilizing machine learning (ML) tools for a wide range of tasks. However, the need for large-scale datasets to train ML models creates challenges for centralized ML…
Daniel Schmid, Christian Jarvers, Heiko Neumann
Advanced computer vision mechanisms have been inspired by neuroscientific findings. However, with the focus on improving benchmark achievements, technical solutions have been shaped by application and engineering constraints. This includes the training of neural networks which led to the development of feature…
Esma Dilek, Murat Dener, Sylvain Girard
As technology continues to develop, computer vision (CV) applications are becoming increasingly widespread in the intelligent transportation systems (ITS) context. These applications are developed to improve the efficiency of transportation systems, increase their level of intelligence, and enhance traffic safety.…
Dawei Zhang, Tingting Yang
Eye tracking is currently a research hotspot in the territory of service robotics. There is an urgent need for machine vision technique in the territory of video surveillance, and biological visual object following is one of the important basic research problems. By tracking the object of interest and recording the…
Filippo Leveni
We propose a feature-based approach for detecting and identifying distorted occurrences of a given template in a scene image by incremental grouping of feature matches between the image and the template. For this purpose, we consider the Delaunay triangulation of template features as an useful tool through which to be…
Pinhe Wang, Jianzhong Qiao, Nannan Liu
To solve the problems existing in the research of scene recognition, this paper studies a new convolutional neural network target detection model to achieve a better balance between the accuracy and speed of high-speed scene image recognition. First, aiming at the problem that the image is easy to be disturbed by…
Wendy Flores-Fuentes, Oleg Sergiyenko, Julio C. Rodríguez-Quiñonez, Jesús E. Miranda-Vega
Information theory is the foundation for computer vision and image processing across diverse applications. It constitutes the application of sophisticated mathematical principles to electrical engineering development for advanced research in vision systems and machine learning. Within this field of study, 3D visual…
Alexander E. Siemenn, Eunice Aissi, Fang Sheng, Armi Tiihonen + 3 more
In materials research, the task of characterizing hundreds of different materials traditionally requires equally many human hours spent measuring samples one by one. We demonstrate that with the integration of computer vision into this material research workflow, many of these tasks can be automated, significantly…
Authors not listed
In experimental chemistry, actions are adjusted based on what we see—such as dosing until dissolution, heating until melting, or stirring until mixing is complete. However, current self-driving labs (SDLs) do not monitor these visual cues. HeinSight 4.0 fills this gap by integrating computer vision into SDLs to enable…
Matteo Dunnhofer, Jean de dieu Uwisengeyimana, Kohitij Kar
How does motion contribute to robust object perception when appearance cues are unreliable? In natural scenes, camouflage, clutter, and occlusion can obscure object boundaries in static images, yet humans often resolve these ambiguities once objects move. Here we ask whether modern artificial vision systems capture…
Paul Linton, Michael J. Morgan, Jenny C. A. Read, Dhanraj Vishwanath + 2 more
'Sarah H. Creem-Regehr' 'Fulvio Domini'] New approaches to 3D vision are enabling new advances in artificial intelligence and autonomous vehicles, a better understanding of how animals navigate the 3D world, and new insights into human perception in virtual and augmented reality. Whilst traditional approaches to 3D…
Rama El-khawaldeh, Mason Guy, Finn Bork, Nina Taherimakhsousi + 6 more
This work presents a generalizable computer vision (CV) and machine learning model that is used for automated real-time monitoring and control of a diverse array of workup processes. Our system simultaneously monitors multiple physical parameters (e.g., liquid level, homogeneity, turbidity, solid, residue, and color)…
Niah Holtz, Evan Lloyd, Chloe Hoff, Alex C. Keene + 1 more
Cichlid fishes have long been a popular model for ecology and evolutionary biology. Not only do they exhibit nearly unparalleled taxonomic diversity, but their community structures are both complex and extremely dense. Niche partitioning along dietary axes has been credited in maintaining cichlid biodiversity in a…
Authors not listed
This work focuses on a novel human-centered digital assistant combining Mixed Reality (MR), Computer Vision and Machine Learning regression to guide professionals and students on how to operate and correctly parameterize battery manufacturing machinery. Our Concept article aim is to provide a proof of concept of our…
Malachy Guzman, Brian Geuther, Gautam Sabnis, Vivek Kumar
Changes in body mass are a key indicator of health and disease in humans and model organisms. Animal body mass is routinely monitored in husbandry and preclinical studies. In rodent studies, the current best method requires manually weighing the animal on a balance which has at least two consequences. First, direct…
Michael Chimento, Alex Hoi Hang Chan, Lucy M. Aplin, Fumihiro Kano
Collection of large behavioral data-sets on wild animals in natural habitats is vital in ecology and evolution studies. Recent progress in machine learning and computer vision, combined with inexpensive microcomputers, have unlocked a new frontier of fine-scale markerless measurements. Here, we leverage these…
Desmond Asante, Shelby Ziccardi, Stephen Guy, Rachel L. Hawe
Assessment of reaching is foundational to upper limb neurorehabilitation. Current neurorehabilitation needs have increased the demand for quantitative clinical assessments of bilateral coordination. Robotics and computer vision for motion tracking are two means to provide relevant quantitative metrics but have many…
Thomas Tsao, Doris Y. Tsao
Title: Significance We address a question at the foundation of natural and artificial vision: how can a visual system segment and track objects? In the real world, objects can undergo drastic changes in appearance due to deformation, perspective change, or dynamic occlusion. For example, an animal moving behind a fence…
Authors not listed
Determining complete atomic structures directly from microscopy images remains a longstanding challenge in materials science. MicroscopyGPT is a vision-language model (VLM) that leverages multimodal generative pre-trained transformers to predict full atomic configurations including lattice parameters, element types…
Pierre Cutellic
This paper focuses on a specific aspect of human visual discrimination from computationally generated solutions for CAAD ends. The bottleneck at work here concern informational ratios of discriminative rates over generative ones. The amount of information that can be brought to a particular sensory modality for human…
Yung-Hao Yang, Taiki Fukiage, Zitang Sun, Shin’ya Nishida
The neural and computational mechanisms underlying visual motion perception have been extensively investigated over several decades, but most studies have used simple artificial stimuli such as random-dot kinematograms. Thus, it remains difficult to predict how human observers perceive optical flows in complex natural…
Authors not listed
Predicting protein-ligand binding affinity from three-dimensional (3D) structural data is a central task in structure-based drug discovery, yet it remains challenging due to limited data availability, structural complexity, and the sparse nature of 3D molecular representations. In this study, we investigate the…
Jingmeng Li, Hui Wei
Visual emergence is the phenomenon in which the visual system obtains a holistic perception after grouping and reorganizing local signals. The picture Dalmatian dog is known for its use in explaining visual emergence. This type of image, which consists of a set of discrete black speckles (speckles), is called an…
Takeshi Uejima, Elena Mancinelli, Ernst Niebur, Ralph Etienne-Cummings
Some animals including humans use stereoscopic vision which reconstructs spatial information about the environment from the disparity between images captured by eyes in two separate adjacent locations. Like other sensory information, such stereoscopic information is expected to influence attentional selection. We…