Research has been ongoing for years to discover image features that enable their best classification. One of the latest developments in this area is the Self-Distillation with No Labels Vision Transformer—DINO-ViT features. However, even for a...
Natural disasters create complex environments where effective human detection is both critical and challenging, especially when individuals are partially occluded. While recent advancements in computer vision have improved detection capabilities, 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...
Agriculture is important for ecology. The early detection and treatment of agricultural crop diseases are meaningful and challenging tasks in agriculture. Currently, the identification of plant diseases relies on manual detection, which has the disad...
Here, we report that Dino, a lncRNA required for p53 signaling, suppresses spontaneous tumorigenesis in mice. Dino−/− mice develop significantly more malignant tumors than Dino+/+ littermate controls, consisting predominantly of sarcomas, B cell lymp...
Inshore synthetic aperture radar (SAR) ship detection remains challenging because strong coastal clutter, speckle noise, and degraded target responses frequently result in false alarms and missed detections of small vessels. Moreover, local scatterin...
Two challenges in computer vision (CV) related to face detection are the difficulty of acquisition in the target domain and the degradation of image quality. Especially in low-light situations, the poor visibility of images is difficult to label, whi...
Portable digital microscopy (PDM) has become standard equipment in archaeological and restoration campaigns. In recent years, several studies have proposed combining PDM and micro-photogrammetry for preliminary documentation and in situ three-dimensi...
Transmission towers are fundamental components of electric power networks. However, their structure, scale and background textures vary substantially across remote sensing images acquired from different geographic regions. These discrepancies often r...
With the rapid development of multi-modal large models, the Visual–Language–Action (VLA) model has gradually become a new paradigm for autonomous robot operations. The VLA model encodes experimental images and text instructions separately...
Accurate segmentation of nuclei and cytoplasm in cervical cytology images plays a pivotal role in characterizing cellular morphology. The primary challenge is to precisely delineate boundaries within densely clustered cells, which is complicated by l...
Infrared small target detection (IRSTD) supports remote-sensing surveillance and early warning, but infrared targets often occupy only a few pixels, exhibit weak appearance cues, and resemble thermal clutter. Vision-language detectors such as Groundi...
The accurate detection and classification of brain tumors from magnetic resonance imaging (MRI) are critical for diagnosis and treatment planning. While deep learning has shown remarkable success in this domain, many state-of-the-art models rely on c...
Object Detection in Complex Indoor Scenes is designed to identify and categorize objects in indoor settings, with applications in areas such as smart homes, security surveillance, and home service robots. It forms the basis for advanced visual tasks...
CLIP-based zero-shot anomaly detection has recently shown strong generalization by aligning visual features with textual normal/abnormal concepts. However, CLIP has essentially been trained for image-level text alignment, making it difficult to ensur...
Weed segmentation is a fundamental task in precision agriculture, essential for targeted intervention and sustainable farming. However, achieving accurate segmentation remains challenging due to the high visual similarity between weeds and crops, as...
Recently, the progress of foundation models such as CLIP and SAM has shown the great potential of zero-shot anomaly detection tasks. However, existing methods usually rely on general descriptions such as “abnormal”, and the semantic cover...
Object detection is a crucial research topic in the fields of computer vision and artificial intelligence, involving the identification and classification of objects within images. Recent advancements in deep learning technologies, such as YOLO (You...
This study presents a zero-shot object detection framework for corner casting detection in shipping container operations, leveraging edge computing for intelligent robotic perception and control. The proposed system integrates Grounding DINO on a Ras...
Road traffic safety facilities (TSFs) are of significant importance in the management and maintenance of traffic safety. The complexity and variety of TSFs make it challenging to detect them manually, which renders the work unsustainable. To achieve...
This study conducted an analysis of zero-shot detection capabilities using two frameworks, YOLO-World and Grounding DINO, on a selection of images in the wild blueberry (Vaccinium angustifolium Ait.) cropping system. The datasets included ripe wild b...
Transformer-based object detection has recently attracted increasing interest and shown promising results. As one of the DETR-like models, DETR with improved denoising anchor boxes (DINO) produced superior performance on COCO val2017 and achieved a n...
Desert encroachment significantly threatens the living and activity space of humanity, and undertaking human-directed vegetation restoration is one of the effective ways to prevent desert expansion. In the process of desert vegetation restoration, co...
Transformer-based methodologies in object detection have recently piqued considerable interest and have produced impressive results. DETR, an end-to-end object detection framework, ingeniously integrates the Transformer architecture, traditionally us...
This research addresses the critical need for efficient image annotation in precision agriculture, using the wild blueberry (Vaccinium angustifolium Ait.) cropping system as a representative application to enable data-driven crop management. Tasks su...
Artificial intelligence (AI) currently exhibits considerable potential within the realm of biodiversity conservation. However, high-quality regionally customized datasets remain scarce, particularly within urban environments. The existing large-scale...
This paper presents a hybrid pipeline based on zero-shot vision models for automatic node count estimation in Lisianthus (Eustoma grandiflorum) cultivation and a system for real-time growth information sharing. The multistage image analysis pipeline...
Growth monitoring of crops is a crucial aspect of precision agriculture, essential for optimal yield prediction and resource allocation. Traditional crop growth monitoring methods are labor-intensive and prone to errors. This study introduces an auto...
Due to its capacity to gather vast, high-level data about human activity from wearable or stationary sensors, human activity recognition substantially impacts people’s day-to-day lives. Multiple people and things may be seen acting in the video...
The marble industry relies on proprietary commercial names rather than objective visual categories, creating market inefficiencies for stakeholders who select stones based on appearance. Supervised classification perpetuates this problem by replicati...
The rapid growth of the cannabis industry necessitates accurate and efficient methods for detecting and classifying cannabis seed varieties, which is crucial for quality control, regulatory compliance, and genetic research. This study presents a deep...
As global climate warming enhances the navigability of Arctic routes, their navigation value has become prominent, yet ships operating in ice-covered waters face severe threats from sea ice and icebergs. Existing manual observation and radar monitori...
Background/Objectives: As reported by the World Health Organization, Mpox (monkeypox) is an important disease present in 110 countries, mostly in South Asia and Africa. The number of Mpox cases has increased rapidly, and the medical world is worried...
Architectural typology classification plays an important role in large-scale documentation and analysis of urban cultural heritage. Recent advances in computer vision enable automated approaches for detecting and categorizing buildings from street-le...
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide. Early and accurate prediction of AD progression is crucial for early intervention and personalized treatment planning. Although AD d...
The extensive application of unmanned aerial vehicle (UAV) technology has increased academic interest in object detection algorithms for UAV images. Nevertheless, these algorithms present issues such as low accuracy, inadequate stability, and insuffi...
20 December 2021
In Italy, drug expenditure governance is achieved by setting caps based on the percentage increase in hospital spending compared to the previous year. This method is ineffective in identifying issues and opportunities as it does not consider an analy...
The risk of relapse for early breast cancer (BC) patients persists even after decades and to date, no specific and sensitive effective circulating biomarker for recurrence prediction has been identified yet. The international guidelines do not recomm...
As autonomous driving technology expands from structured urban roads to unstructured outdoor environments, precise understanding of complex terrain has become a critical requirement for ensuring safe vehicle navigation. However, outdoor environments...
Neuroendocrine tumors (NETs) are rare neoplasms frequently characterized by an upregulation of the mammalian rapamycin targeting (mTOR) pathway resulting in uncontrolled cell proliferation. The mTOR pathway is also involved in skeletal muscle protein...
Remote sensing provides vast unlabeled imagery at low cost, yet annotation remains expensive, making self-supervised learning (SSL) well suited to this domain. However, existing DINO-style SSL frameworks are not well suited to remote sensing imagery,...
Chemically speaking, polymers are multi-molecular compounds that have specific physicochemical properties. Hair cosmetics utilize their ability to create a protective film and make the cosmetic formulation more viscous, which facilitates its applicat...
Accurate detection of small transmission towers in remote sensing images is critical for low-altitude aviation safety and power-grid monitoring, yet it remains challenging due to complex backgrounds, weak target responses, and severe feature submersi...
2 December 2024
Research and applications in artificial intelligence have recently shifted with the rise of large pretrained models, which deliver state-of-the-art results across numerous tasks. However, the substantial increase in parameters introduces a need for p...
The factors affecting the self-assembly process in low molecular weight gelators (LMWGs) were investigated by tuning the gelation properties of a well-known gelator N-(4-pyridyl)isonicotinamide (4PINA). The N―H∙∙∙N interactions responsible for gel fo...
Borehole detection in textured quarry reconstructions is challenging because shadows, rocks, and fractured ground can resemble visible surface openings. We introduce GeoBoreNet, which augments RGB with four pixel-aligned inputs derived from reconstru...
The dinoflagellate Symbiodiniaceae family plays a central role in the health of the coral reef ecosystem via the symbiosis that establishes with its inhabiting cnidarians and supports the host metabolism. In the last few decades, coral reefs have bee...
SPX domain-containing proteins (SPXc) are crucial for regulating phosphorus (P) homeostasis in plants. Recently, the SPX gene was identified in the diatom model Phaeodactylum tricornutum and shown to serve as a negative regulator of P acquisition. Wh...
Vision Transformers (ViTs) have achieved remarkable success; however, their internal decision-making mechanisms remain largely opaque. The Dynamic Accumulated Attention Map (DAAM) has emerged as a prominent interpretability tool that visualizes model...
Background: Rapid population aging poses significant challenges to health and wellness systems, necessitating innovative technological interventions. Smart home technologies, particularly voice-activated intelligent assistants (smart speakers), repre...
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