Video surveillance systems have become pervasive in contemporary society, prompting growing concerns about their psychological and behavioral effects on individuals. This study investigates how perceived surveillance influences self-censorship and be...
Panoptic segmentation combines instance and semantic predictions, allowing the detection of countable objects and different backgrounds simultaneously. Effectively approaching panoptic segmentation in remotely sensed data is very promising since it p...
A panoptic segmentation network to predict masks and classes for things and stuff in images is proposed in this work. Recently, panoptic segmentation has been advanced through the combination of the query-based learning and end-to-end learning approa...
Fast and accurate semantic scene understanding is essential for mobile robots to operate in complex environments. An emerging research topic, panoptic segmentation, serves such a purpose by performing the tasks of semantic segmentation and instance s...
Panoptic segmentation, as a key task in the field of computer vision, holds significant importance in practical applications such as autonomous driving and robot vision. Currently, among deep-learning-based panoptic segmentation methods, query-based...
Unauthorized farmland excavation is a prominent manifestation of farmland non-agriculturalization, and its effective monitoring depends on structured representations of objects and their spatial interactions in complex scenes. However, the existing c...
Satellite remote sensing images contain complex and diverse ground object information and the images exhibit spatial multi-scale characteristics, making the panoptic segmentation of satellite remote sensing images a highly challenging task. Due to th...
Panoptic segmentation, a pivotal research direction in computer vision, unifies pixel-level object and background recognition within a scene, crucial for applications like autonomous driving. However, existing methods, including State-of-the-Art mode...
Panoptic scene graph generation (PSG) aims to simultaneously segment both foreground objects and background regions while predicting object relations for fine-grained scene modeling. Despite significant progress in panoptic scene understanding, curre...
Teeth segmentation plays a pivotal role in dentistry by facilitating accurate diagnoses and aiding the development of effective treatment plans. While traditional methods have primarily focused on teeth segmentation, they often fail to consider the b...
This paper reconstructs the archive of Islamic humanism as a cultural resource for Critical Psychologists, addressing the geopolitical double-bind of the global Muslim population caught between Islamophobia and fundamentalism. This living archive spa...
This study proposes a clinically driven hybrid segmentation framework for dense breast tissue analysis in mammographic images, addressing persistent challenges associated with intensity inhomogeneity, low-contrast, and complex tumor morphology. The f...
Highway landscape quality is important for visual comfort, environmental coordination, and infrastructure management. However, conventional assessment methods rely heavily on manual inspection and qualitative judgment, which are subjective and ineffi...
Collaboration among road agents, such as connected autonomous vehicles and roadside units, enhances driving performance by enabling the exchange of valuable information. However, existing collaboration methods predominantly focus on perception tasks...
Transportation panoptic perception (TPP) is a fundamental capability for both on-board and roadside monitoring systems. In this paper, we propose an end-to-end lightweight multitask model, MT-TPPNet, which jointly performs three tasks: object detecti...
Visible greenery is widely considered beneficial in urban design, but it is less clear whether adding more greenery to the same view always improves restorative appraisal. This study tested that question using matched three-dimensional scenes. Nine F...
Vision-based 3D human pose estimation approaches are typically evaluated on datasets that are limited in diversity regarding many factors, e.g., subjects, poses, cameras, and lighting. However, for real-life applications, it would be desirable to cre...
Recent advancements in image segmentation have been notably driven by Vision Transformers. These transformer-based models offer one versatile network structure capable of handling a variety of segmentation tasks. Despite their effectiveness, the purs...
Universal image segmentation aims to handle all segmentation tasks within a single model architecture and ideally requires only one training phase. To achieve task-conditioned joint training, a task token needs to be used in the multi-task training t...
Page stream segmentation (PSS) is the task of retrieving the boundaries that separate source documents given a consecutive stream of documents (for example, sequentially scanned PDF files). The task has recently gained more interest as a result of th...
Fully convolutional structures provide feature maps acquiring local contexts of an image by only stacking numerous convolutional layers. These structures are known to be effective in modern state-of-the-art object detectors such as Faster R-CNN and S...
Instance segmentation in high-resolution images is essential for applications such as remote sensing, medical imaging, and precision agriculture, yet remains challenging due to factors such as small object sizes, irregular shapes, and occlusions. Til...
As the main area for photosynthesis in trees, the canopy absorbs a large amount of carbon dioxide and plays an irreplaceable role in regulating the carbon cycle in the atmosphere and mitigating climate change. Therefore, monitoring the growth of the...
To address the issue of low segmentation accuracy for small objects in the Mask Dino segmentation method, we propose an improved small object segmentation model called FFMask Dino. Initially, we introduce scaled cosine attention and the log-cpb metho...
Accurate and timely crop mapping supports agricultural resource management, yield prediction, and food security decision-making. In this study, we propose the Temporal Multi-scale Spatio-Temporal Network (TMST), a crop mapping method that integrates...
Cervical range of motion (CROM) has been used in research and clinically for assessing cervical health. Gold-standard goniometers tend to be cumbersome. However, Inertial Measurement Units (IMUs) or vision-based alternatives demand frequent calibrati...
Agricultural factories utilize advanced facilities and technologies to cultivate crops in a controlled environment, enhancing operational yields and reducing reliance on natural resources. This is crucial for ensuring a stable supply of agricultural...
Neutrophils are central executors of innate immunity. Yet murine models are inherently limited by low baseline neutrophil counts. NSG mice are among the most widely used models for xenotransplantation and studies on the humanized immune system. Altho...