22 papers · ranked by Valyu relevance
Jun Shu, Juncheng He, Ling Li
Infrared image of power equipment is widely used in power equipment fault detection, and segmentation of infrared images is an important step in power equipment thermal fault detection. Nevertheless, since the overlap of the equipment, the complex background, and the low contrast of the infrared image, the current…
Min Bai, Raquel Urtasun
Most contemporary approaches to instance segmentation use complex pipelines involving conditional random fields, recurrent neural networks, object proposals, or template matching schemes. In this paper, we present a simple yet powerful end-to-end convolutional neural network to tackle this task. Our approach combines…
Mingzhu Liu, Wei Zhang, Haoran Wei, Marco Leo
Video instance segmentation, a key technology for intelligent sensing in visual perception, plays a key role in automated surveillance, robotics, and smart cities. These scenarios rely on real-time and efficient target-tracking capabilities for accurate perception and intelligent analysis of dynamic environments.…
Ruben Panero Martinez, Ionut Schiopu, Bruno Cornelis, Adrian Munteanu
The paper proposes a novel instance segmentation method for traffic videos devised for deployment on real-time embedded devices. A novel neural network architecture is proposed using a multi-resolution feature extraction backbone and improved network designs for the object detection and instance segmentation branches.…
Lin Shao, Ye Tian, Jeannette Bohg
— We propose a method for instance-level segmentation that uses RGB-D data as input and provides detailed information about the location, geometry and number of individual objects in the scene. This level of understanding is fundamental for autonomous robots. It enables safe and robust decisionmaking under the large…
Jingru Yi, Hui Tang, Pengxiang Wu, Bo Liu + 4 more
'Dimitris Metaxas' 'Lianyi Han' 'Wei Fan'] Instance segmentation of biological images is essential for studying object behaviors and properties. The challenges, such as clustering, occlusion, and adhesion problems of the objects, make instance segmentation a non-trivial task. Current box-free instance segmentation…
Anuradha Kar, Manuel Petit, Yassin Refahi, Guillaume Cerutt + 2 more
Segmenting three dimensional microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed which claim to provide high accuracy segmentation of cellular images and are increasingly…
Linjie Yang, Yuchen Fan, Ning Xu
In this paper we present a new computer vision task, named video instance segmentation. The goal of this new task is simultaneous detection, segmentation and tracking of instances in videos. In words, it is the first time that the image instance segmentation problem is extended to the video domain. To facilitate…
Kaiyue Du, Jin Meng, Xin Meng, Shifeng Wang + 2 more
'Arturo de la Escalera Hueso'] Fine-grained urban environment instance segmentation is a fundamental and important task in the field of environment perception for autonomous vehicles. To address this goal, a model was designed with LiDAR pointcloud data and camera image data as the subject of study, and the reliability…
Farnoosh Arefi, Amir M. Mansourian, Shohreh Kasaei, Yawen Lu
Recently, there has been growing interest in deep spectral methods for image localization and segmentation, influenced by traditional spectral segmentation approaches. These methods reframe the image decomposition process as a graph partitioning task by extracting features using self-supervised learning and utilizing…
Tomas Vicar, Jiri Chmelik, Roman Jakubicek, Larisa Chmelikova + 4 more
In this paper, U-Net-based method for robust adherent cell segmentation for quantitative phase microscopy image is designed and optimised. We designed and evaluated four specific post-processing pipelines. To increase the transferability to different cell types, non-deep learning transfer with adjustable parameters is…
Lei Yang, Yan Wei, Yisheng He, Wei Sun + 3 more
'Haibin Huang' 'Haoqiang Fan'] In this paper, we introduce a brand new dataset to promote the study of instance segmentation for objects with irregular shapes. Our key observation is that though irregularly shaped objects widely exist in daily life and industrial scenarios, they received little attention in the…
Yuxing Wang, Junhan Zhao, Hongye Xu, Cheng Han + 5 more
Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation and instance segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform…
Laura Antonelli, Valentina De Simone, Daniela di Serafino
Image segmentation is a central topic in image processing and computer vision and a key issue in many applications, e.g., in medical imaging, microscopy, document analysis and remote sensing. According to the human perception, image segmentation is the process of dividing an image into non-overlapping regions. These…
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)…
Julian Hennies, José Miguel Serra Lleti, Constantin Pape, Sultan Bekbayev + 3 more
Segmentation of large-volume datasets obtained by volume SEM techniques is a challenging task that generally requires a considerable amount of human effort. Despite recent advances in deep learning leading to the successful segmentation of cellular organelles in a variety of datasets, it is still challenging and…
Matthias Arzt, Joran Deschamps, Christopher Schmied, Tobias Pietzsch + 3 more
We present Labkit, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to single- and multi-channel images as well as to timelapse movies in 2D or 3D. Labkit is specifically designed to work…
Andreea Gurita, Irina Georgiana Mocanu, Guillermo Villanueva, Evangelia I. Zacharaki
'Evangelia I. Zacharaki'] Image segmentation is an essential step in image analysis that brings meaning to the pixels in the image. Nevertheless, it is also a difficult task due to the lack of a general suited approach to this problem and the use of real-life pictures that can suffer from noise or object obstruction.…
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…
Sandra Jardim, João António, Carlos Mora, Xiaohao Cai + 2 more
'Gaohang Yu'] With a wide range of applications, image segmentation is a complex and difficult preprocessing step that plays an important role in automatic visual systems, which accuracy impacts, not only on segmentation results, but directly affects the effectiveness of the follow-up tasks. Despite the many advances…
Yichen He, Marco Camaiti, Lucy E. Roberts, James M. Mulqueeney + 2 more
The increased availability of 3D image data requires improving the efficiency of digital segmentation, currently relying on manual labelling, especially when separating structures into multiple components. Automated and semi-automated methods to streamline segmentation have been developed, such as deep learning and…
Kohulan Rajan, Henning Otto Brinkhaus, M. Isabel Agea, Achim Zielesny + 1 more
The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that…