Feature selection is a promising dimension reduction technology that focuses on a reduced subspace by selecting excellent features. Most existing approaches tend to emphasize the discriminative ability of features based on either a global or a local...
Instance segmentation has been developing rapidly in recent years. Mask R-CNN, a two-stage instance segmentation approach, has demonstrated exceptional performance. However, the masks are still very coarse. The downsampling operation of the backbone...
In banks, governments, and Internet companies, inconsistent data problems may often arise when various information systems are collecting, processing, and updating data due to human or equipment reasons. The emergence of inconsistent data makes it im...
Multi-view engineering uses heterogeneous models to represent complementary system concerns, but independent model evolution can introduce cross-view inconsistencies. This paper presents MVCL (Multi-View Constraint Language), a domain-specific langua...
A single-valued neutrosophic set is an instance of a neutrosophic set, which provides us an additional possibility to represent uncertainty, imprecise, incomplete and inconsistent information existing in real situations. In this research study, we pr...
Contrastive image representation learning has been essential for pre-training vision foundation models to deliver excellent transfer learning performance. It was originally developed based on instance discrimination, which focuses on instance-level r...
This review summarizes randomized controlled trials (RCTs) assessing the effect of docosahexaenoic acid (DHA) supplementation in the first 1000 days on child language. Six databases were searched and RCTs were included if they involved supplementatio...
Pre-trained code models are increasingly used in software engineering, yet their incremental value beyond traditional software metrics for future-version class-level defect prediction remains unclear. This study evaluates CodeBERT, GraphCodeBERT, and...
This study addresses the side effect of the rapid development of the Internet, positioning botnets within digital ecosystems as a very serious potential threat to the Internet users. Malicious web robot might facilitate Web/data scraping, DDoS attack...
To address the variability and complexity of attack types, this paper proposes a multi-instance zero-watermarking algorithm that goes beyond the conventional one-to-one watermarking approach. Inspired by the class-instance paradigm in object-oriented...
To address issues commonly observed during the inference phase of large language models—such as inconsistent labels, formatting errors, or semantic deviations—a series of targeted strategies has been proposed. First, a relation label refi...
Availability of domain-specific datasets is an essential problem in object detection. Datasets of inshore and offshore maritime vessels are no exception, with a limited number of studies addressing maritime vessel detection on such datasets. For that...
Relation classification (RC) is an important task in information extraction from unstructured text. Recently, several neural methods based on various network architectures have been adopted for the task of RC. Among them, convolution neural network (...
Background/Objectives: Endoscopic airway imaging, used in endoscopy-guided airway management, enables geometry-based assessment of the airways. However, COCO-format datasets often include fragmented regions and geometrically inconsistent polygon anno...
We consider the peculiarity of unique events, such as those of a natural, evolutionary, and social nature. In particular, we consider unique social events that have had either the claim or the vocation of being salvific for humanity, such as the intr...
Object detection in optical remote sensing imagery faces persistent challenges from severe instance overlap, extreme spatial density, and motion or atmospheric blur. These degradations cause conventional detectors to over-mix neighboring instance fea...
The roll-to-roll manufacturing system is extensively used for mass producing products made of plastic, paper, and fabric in several traditional industries. When flexible substrates, also known as webs, are heated and transported inside the dryer, an...
Occluded person re-identification (Re-ID) faces significant challenges, mainly due to the interference of occlusion noise and the scarcity of realistic occluded training data. Although data augmentation is a commonly used solution, the current occlus...
The Neutrosophic set (NS) has grasped concentration by its ability for handling indeterminate, uncertain, incomplete, and inconsistent information encountered in daily life. Recently, there have been various extensions of the NS, such as single value...
Discarding Non-Maximum Suppression (NMS) post-processing and realizing fully end-to-end object detection is a recent research focus. Previous works have proved that the one-to-one label assignment strategy provides the chance to eliminate NMS during...
Sperm morphology assessment plays a vital role in semen analysis and the diagnosis of male infertility. By quantitatively analyzing the morphological characteristics of the sperm head, midpiece, and tail, it provides essential insights for assisted r...
Large-scale engineering of the 3D scenes used in BIM, GIS, digital twins, and geospatial web delivery frequently suffer from significant geometric redundancy after export to mesh-based delivery formats, arising in part from the inconsistent reuse of...
Recent computer vision techniques based on convolutional neural networks (CNNs) are considered state-of-the-art tools in weed mapping. However, their performance has been shown to be sensitive to image quality degradation. Variation in lighting condi...
Regressing the 3D orientation of a symmetric object with a signed rotation representation is ill posed: the rotations that render an indistinguishable image form an equivalence class, so physically identical poses receive inconsistent labels. This is...
Genome editing using the CRISPR/Cas9 system is one of the trendiest methodologies in the scientific community. Many genome editing approaches require recombinant Streptococcus pyogenes Cas9 (SpCas9) at some point during their application, for instanc...
This paper captures some of the emerging consensus points that came out of the workshop “Mineral Resources in Life Cycle Impact Assessment: Mapping the path forward”, held at the Natural History Museum London on 14 October 2015: that current practice...
This review discusses the implications, from a new researcher’s perspective, of variations in the design, dose and participant age group used and their subsequent effects on the cognitive performance and mood observed in studies investigating t...
Granulocyte colony-stimulating factor (G-CSF) has been suggested as a supplementary approach for endometrial preparation in IVF. Clinical results continue to be inconsistent. This narrative review synthesises molecular and clinical information to elu...
Deep-learning-based land cover segmentation models for high-resolution aerial images often suffer from inconsistent performance on unseen data due to limited spatial and temporal dataset ranges alongside inherent labeling inconsistencies. Existing so...
This study re-examines the balance between architectural intricacy and generalization in Transformer models for long-term time series predictions. We perform a systematic comparison involving a lightweight baseline (iTransformer) and two enhanced ver...
The progress of incorporating deep learning in the field of medical image interpretation has been greatly hindered due to the tremendous cost and time associated with generating ground truth for supervised machine learning, alongside concerns about t...
Temporal action detection (TAD) aims to localize and recognize action instances in untrimmed videos, and serves as a key component in practical intelligent electronic systems such as smart video surveillance and real-time human–machine interact...
Despite the pivotal role of unmanned aerial vehicles (UAVs) in intelligent inspection tasks, existing video instance segmentation methods struggle with irregular deforming targets, leading to inconsistent segmentation results due to ineffective featu...
Human cervical cancer and pre-cancer research relies on datasets scattered across modality-specific archives, imaging repositories, benchmark platforms, trial registries, and controlled-access catalogs. This fragmentation—combined with heteroge...
This paper proposes a data preparation process for managing real-world kinematic data and detecting fishing vessels. The solution is a binary classification that classifies ship trajectories into either fishing or non-fishing ships. The data used are...
A description of Likert scales can be given using the multipoles technique known in quantum physics and applied to behavioral sciences data. This paper considers decomposition of Likert scales by the multipoles for the application of decreasing the r...
Transfer-RNA-derived fragments (tRFs) are a relatively recently discovered class of non-coding RNAs derived from both precursor and mature transfer RNAs (tRNAs). Research on these molecules has been expanding rapidly, revealing their diverse roles in...
22 January 2015
Humans are increasingly exposed to nanoparticles (NPs) in medicine and in industrial settings, where significant concentrations of NPs are common. However, NP interactions with and effects on biomolecules and organisms have only recently been address...
Neural machine translation (NMT) typically relies on a substantial number of bilingual parallel corpora for effective training. Mongolian, as a low-resource language, has relatively few parallel corpora, resulting in poor translation performance. Dat...
Dynamic environments pose significant challenges for visual SLAM, including feature ambiguity, weak textures, and map inconsistencies caused by moving objects. We present a robust SLAM framework integrating image enhancement, a mixed-precision quanti...
Despite the increasing volume of research exploring the impact of various characteristics of urban green spaces (UGS) on land surface temperature (LST), findings remain inconsistent, particularly in arid climatic zones. In this research, we examined...
To resolve the issue of state of charge (SOC) inconsistency among energy storage units under traditional equal-power allocation strategies, this paper proposes a multi-unit SOC balancing control strategy based on battery life degradation characterist...
The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime factor for patient risk stratification, although it suffers from inco...
In real-world machine learning scenarios, training data are frequently weakly annotated and distributionally misaligned with deployment environments. Specifically, label ambiguity may arise when each instance is associated with a set of candidate lab...
The OpenStreetMap (OSM) project is an open-source, community-based, user-generated street map/data service. It is the most popular project within the state of the art for crowdsourcing. Although geometrical features and tags of annotations in OSM are...
Historically, the management of bilateral Wilms tumor (BWT) was non-standardized and suffered from instances of prolonged chemotherapy and inconsistent surgical management which resulted in suboptimal renal and oncologic outcomes. Because of the risk...
Artificial intelligence (AI) has shown promising performance in brain tumor diagnosis and prognosis; however, most reported advances remain difficult to translate into clinical practice due to limited interpretability, inconsistent evaluation protoco...
This review studies the potential relationship between the pathogenesis of allergic rhinitis (AR) and otitis media with effusion (OME) in both adults and children, applying the modified Bradford Hill criteria. While AR and OME are distinct conditions...
Epidemiological studies have shown that the prevalence of diabetic peripheral neuropathy (DPN) will increase. Currently, DPN is treated medically. In many instances, the outcome is less than satisfactory, and the treatment is associated with side eff...
Sentiment classification often relies on costly in-domain annotations, while weak-supervision sources provide low-cost but inconsistent labels. We propose Multi-Source Reliability-Aware Aggregation and Cross-domain Consistency Learning (MSRA-CCL) for...
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