Preserving long-tail, minority information during model compression has been linked to algorithmic fairness considerations. However, this assumes that large models capture long-tail information and smaller ones do not, which raises two questions. One...
In long-tail scenarios, models have a very high demand for high-quality data. Information augmentation, as an important class of data-centric methods, has been proposed to improve model performance by expanding the richness and quantity of samples in...
In the field of computer vision, training a well-performing model on a dataset with a long-tail distribution is a challenging task. To address this challenge, image resampling is usually introduced as a simple and effective solution. However, when pe...
When trained on long-tailed distributions, deep neural networks often suffer performance degradation and model bias due to the dominance of head classes. Existing reweighting and sampling strategies have significant limitations, such as reliance on f...
Food classification serves as the basic step of image-based dietary assessment to predict the types of foods in each input image. However, foods in real-world scenarios are typically long-tail distributed, where a small number of food types are consu...
Bearings are essential rotational components that enable mechanical equipment to operate effectively. In real-world industrial environments, bearings are subjected to high temperatures and loads, making failure prediction and health management critic...
Long-tailed data distribution (i.e., minority classes occupy most of the data, while most classes have very few samples) is a common problem in image classification. In this paper, we propose a novel multimodal framework for long-tailed data recognit...
Motivation: Chest X-ray (CXR) is a routine diagnostic X-ray examination for checking and screening various diseases. Automatically localizing and classifying diseases from CXR as a detection task is of much significance for subsequent diagnosis and t...
Real-world datasets often follow a long-tailed distribution, where a few majority (head) classes contain a large number of samples, while many minority (tail) classes contain significantly fewer samples. This imbalance creates an information disparit...
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Channelizing product sales with the aid of Recommender Systems is ubiquitous in e-commerce firms. Recommender systems help consumers by reducing their search cost by directing them to interesting and useful products. It also helps e commerce firms by...
The long-tailed goral is close to extinction, and ex situ conservation is essential to prevent this phenomenon. Studies on the gut microbiome of the long-tailed goral are important for understanding the ecology of this species. We amplified DNA from...
To solve the problem that the common long-tailed classification method does not use the semantic features of the original label text of the image, and the difference between the classification accuracy of most classes and minority classes are large,...
The long-tailed goral (Naemorhedus caudatus) is an endangered species found in the mountains of eastern and northern Asia. Its populations have declined for various reasons, and this species has been designated as legally protected in South Korea. Al...
Bartonella quintana is a zoonotic pathogen with a worldwide distribution. Humans and non-human primates are considered to be natural reservoir hosts for B. quintana. However, information on the molecular epidemiology of this organism is very limited...
In real-world visual recognition tasks, long-tailed distributions pose a widespread challenge, with extreme class imbalance severely limiting the representational learning capability of deep models. In practice, due to this imbalance, deep models oft...
With the rapid development of remote sensing technology, the application of convolutional neural networks in remote sensing object detection has become very widespread, and some multimodal feature fusion networks have also been proposed in recent yea...
In real-world visual recognition tasks, long-tailed distribution is a pervasive challenge, where the extreme class imbalance severely limits the representation learning capability of deep models. Although supervised learning has demonstrated certain...
Arctic Russia is home to more than 90% of all Long-tailed Ducks in the Clangula hyemalis species from the Western Siberia/Northern Europe population. The breeding population in European Russia was estimated to be about 5 million birds in the 1960s, w...
The long-tailed duck (Clangula hyemalis) is a vulnerable and declining species wintering in the Baltic Sea. The introduction of the invasive fish, the round goby (Neogobius melanostomus), dramatically impacted the benthic macrofauna in hard-bottom ha...
With the rapid increase in data scale, real-world datasets tend to exhibit long-tailed class distributions (i.e., a few classes account for most of the data, while most classes contain only a few data points). General solutions typically exploit clas...
Large-scale facial expression datasets are primarily composed of real-world facial expressions. Expression occlusion and large-angle faces are two important problems affecting the accuracy of expression recognition. Moreover, because facial expressio...
The long-tailed goral (Naemorhedus caudatus) faces significant threats from habitat loss and fragmentation and is classified as a Class I endangered species by the Ministry of Environment in South Korea and vulnerable by the IUCN. Understanding the b...
The long-tailed goral (Naemorhedus caudatus) is classified as an endangered species globally, and national projects for conservation are underway in South Korea. However, blood test references would enable comprehensive health assessments in this spe...
Long-tailed image classification remains challenging for vision–language models. Head classes dominate training while tail classes are underrepresented and noisy, and short prompts with weak text supervision further amplify head bias. This pape...
The performance of semantic segmentation in remote sensing, based on deep learning models, depends on the training data. A commonly encountered issue is the imbalanced long-tailed distribution of data, where the head classes contain the majority of s...
Convolutional neural networks have been widely used in remote sensing classification and achieved quite good results. Most of these methods are based on datasets with relatively balanced samples, but such ideal datasets are rare in applications. Long...
Background: Leptospirosis is a zoonotic disease that is ubiquitously distributed and is classified as a re-emerging infectious disease in humans and animals. Many serovars are carried by wildlife; all of them are capable of causing illness in humans....
Climate simulation is often used for evaluation of the sustainability of a species in global scale but not applicable for our study because the global data is too coarse to be used in small and fragmented habitat areas. We examined a weather forecast...
With their advantages in wildlife surveys and biodiversity monitoring, camera traps are widely used, and have been used to gather massive amounts of animal images and videos. The application of deep learning techniques has greatly promoted the analys...
Metagenomics has demonstrated its capability in outbreak investigations and pathogen surveillance and discovery. With high-throughput and effective bioinformatics, many disease-causing agents, as well as novel viruses of humans and animals, have been...
Due to its increasing incidence, skin cancer, and especially melanoma, is considered a major public health issue. Manually detecting skin lesions (SL) from dermoscopy images is a difficult and time-consuming process. Thus, researchers designed comput...
The Staphylococcus (S.) aureus complex, including methicillin-resistant S. aureus (MRSA) and methicillin-susceptible S. aureus (MSSA), and S. argenteus are bacterial pathogens that are responsible for both human and animal infection. However, insight...
As the most commonly used attack strategy by Botnets, the Domain Generation Algorithm (DGA) has strong invisibility and variability. Using deep learning models to detect different families of DGA domain names can improve the network defense ability a...
Microplastic pollution is a global concern arising from the extensive production and use of plastics. The prevalence of microplastics (MPs) in the environment is escalating due in large part to the excessive use of plastics in various human-related a...
Distantly Supervised Relation Extraction (DSRE) aims to automatically identify semantic relationships within large text corpora by aligning with external knowledge bases. Despite the success of current methods in automating data annotation, they intr...
Conspicuousness increases the risk of predation. One strategy to reduce this risk is to increase vigilance. We investigated the frequency of head movements as a measure of vigilance at waterholes in two related songbird species that differed in their...
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Automatic species recognition plays a key role in intelligent agricultural production management and the study of species diversity. However, fine-grained species recognition is a challenging task due to the quite diverse and subtle interclass differ...
The Myoviridae phage tail is a common component of contractile injection systems (CISs), essential for exerting contractile function and facilitating membrane penetration of the inner tail tube. The near-atomic resolution structures of the Myoviridae...
Object detection can accurately identify and locate targets in images, serving basic industries such as agricultural monitoring and urban planning. However, targets in remote sensing images have random rotation angles, which hinders the accuracy of r...
This paper presents a methodology for indirectly estimating the scale of seabird bycatch using existing data. The study focuses on five key species of ducks that winter in the Polish waters of the Baltic Sea and are highly susceptible to bycatch: Lon...
Human parsing is an important technology in human–robot interaction systems. At present, the distribution of multi-category human parsing datasets is unbalanced, and the samples present a long-tailed distribution, which directly affects the per...
Knowledge graph-enhanced recommendation has gained increasing attention for its ability to provide structured semantic context. However, most existing approaches struggle with two critical challenges: the sparsity of long-tail relations in knowledge...
The Geographic Knowledge Graph (GeoKG) serves as an effective method for organizing geographic knowledge, playing a crucial role in facilitating semantic interoperability across heterogeneous data sources. However, existing GeoKGs are limited by a la...
The contraception-based approach to wildlife management is a humane and effective alternative to population control methods. Wildlife management only has a few conventional ways to control overpopulation, such as culling, translocation, poisoning, an...
Accurate global crop type mapping is essential to ensure food security. However, large-scale crop-type mapping still poses challenges to commonly used classification strategies. Specifically, variation within crop types downgrades classification perf...
With the rapid development of remote sensing technology, satellites can now capture multispectral (MS) and panchromatic (PAN) images simultaneously. MS images offer rich spectral details, while PAN images provide high spatial resolutions. Effectively...
Raw image classification datasets generally maintain a long-tailed distribution in the real world. Standard classification algorithms face a substantial issue because many labels only relate to a few categories. The model learning processes will tend...
Owing to their similarities to humans in various aspects, non-human primates (NHPs) serve as valuable translational models that has greatly contributed to scientific advancements. However, working with untrained NHPs can cause stress and increase the...
Pavement distress data in a single section usually presents a long-tailed distribution, with potholes, sealed cracks, and other distresses normally located at the tail. This distribution will seriously affect the performance and robustness of big dat...
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