Papers Image Categorization
“Image Categorization” 태그가 달린 논문 61편 · 필터 해제
A novel approach towards the classification of Bone Fracture from Musculoskeletal Radiography images using Attention Based Transfer Learning
Computer-aided diagnosis (CAD) is today considered a vital tool in the field of biological image categorization, segmentation, and other related tasks. The current breakthrough in computer vision algorithms and deep lear…
Fracture detectionImage CategorizationMedical Image AnalysisTransfer LearningTowards Zero-Shot Camera Trap Image Categorization
This paper describes the search for an alternative approach to the automatic categorization of camera trap images. First, we benchmark state-of-the-art classifiers using a single model for all images. Next, we evaluate m…
Image CategorizationExploring Social Media Image Categorization Using Large Models with Different Adaptation Methods: A Case Study on Cultural Nature's Contributions to People
Social media images provide valuable insights for modeling, mapping, and understanding human interactions with natural and cultural heritage. However, categorizing these images into semantically meaningful groups remains…
DiversityImage CategorizationText-Guided Mixup Towards Long-Tailed Image Categorization
In many real-world applications, the frequency distribution of class labels for training data can exhibit a long-tailed distribution, which challenges traditional approaches of training deep neural networks that require …
Ensemble LearningFew-Shot LearningImage CategorizationFungiTastic: A multi-modal dataset and benchmark for image categorization
We introduce a new, challenging benchmark and a dataset, FungiTastic, based on fungal records continuously collected over a twenty-year span. The dataset is labeled and curated by experts and consists of about 350k multi…
ClassificationFew-Shot LearningImage CategorizationMulti-modal Classification+1A challenge in A(G)I, cybernetics revived in the Ouroboros Model as one algorithm for all thinking
A topical challenge for algorithms in general and for automatic image categorization and generation in particular is presented in the form of a drawing for AI to understand. In a second vein, AI is challenged to produce …
AllImage CategorizationFoveated Retinotopy Improves Classification and Localization in CNNs
From a falcon detecting prey to humans recognizing faces, many species exhibit extraordinary abilities in rapid visual localization and classification. These are made possible by a specialized retinal region called the f…
ClassificationImage Categorizationimage-classificationImage Classification+2On the Image-Based Detection of Tomato and Corn leaves Diseases : An in-depth comparative experiments
The research introduces a novel plant disease detection model based on Convolutional Neural Networks (CNN) for plant image classification, marking a significant contribution to image categorization. The innovative traini…
Image Categorizationimage-classificationImage ClassificationPipeline Enabling Zero-shot Classification for Bangla Handwritten Grapheme
This research investigates Zero-Shot Learning (ZSL), and proposes CycleGAN-based image synthesis and accurate label mapping to build a strong association between labels and graphemes. The objective is to enhance model ac…
Bangla Text DetectionClassificationGrapheme DetectionHandwritten Text Recognition+7Evaluating the Reliability of CNN Models on Classifying Traffic and Road Signs using LIME
The objective of this investigation is to evaluate and contrast the effectiveness of four state-of-the-art pre-trained models, ResNet-34, VGG-19, DenseNet-121, and Inception V3, in classifying traffic and road signs with…
Image CategorizationSpatial encoding of BOLD fMRI time series for categorizing static images across visual datasets: A pilot study on human vision
Functional MRI (fMRI) is widely used to examine brain functionality by detecting alteration in oxygenated blood flow that arises with brain activity. In this study, complexity specific image categorization across differe…
Image CategorizationMulti-class ClassificationTime SeriesSR-GNN: Spatial Relation-aware Graph Neural Network for Fine-Grained Image Categorization
Over the past few years, a significant progress has been made in deep convolutional neural networks (CNNs)-based image recognition. This is mainly due to the strong ability of such networks in mining discriminative objec…
Fine-Grained Image ClassificationGraph Neural NetworkHuman-Object Interaction DetectionImage Categorization+2Predicting skull fractures via CNN with classification algorithms
Computer Tomography (CT) images have become quite important to diagnose diseases. CT scan slice contains a vast amount of data that may not be properly examined with the requisite precision and speed using normal visual …
ClassificationImage CategorizationCDNet: Contrastive Disentangled Network for Fine-Grained Image Categorization of Ocular B-Scan Ultrasound
Precise and rapid categorization of images in the B-scan ultrasound modality is vital for diagnosing ocular diseases. Nevertheless, distinguishing various diseases in ultrasound still challenges experienced ophthalmologi…
DisentanglementImage CategorizationLearning an Adaptation Function to Assess Image Visual Similarities
Human perception is routinely assessing the similarity between images, both for decision making and creative thinking. But the underlying cognitive process is not really well understood yet, hence difficult to be mimicke…
Image CategorizationImage Similarity SearchMetric LearningRetrievalUltrafast Image Categorization in Biology and Neural Models
Humans are able to categorize images very efficiently, in particular to detect the presence of an animal very quickly. Recently, deep learning algorithms based on convolutional neural networks (CNNs) have achieved higher…
Image CategorizationClassifications of Skull Fractures using CT Scan Images via CNN with Lazy Learning Approach
Classification of skull fracture is a challenging task for both radiologists and researchers. Skull fractures result in broken pieces of bone, which can cut into the brain and cause bleeding and other injury types. So it…
ClassificationImage CategorizationModeling Temporal Concept Receptive Field Dynamically for Untrimmed Video Analysis
Event analysis in untrimmed videos has attracted increasing attention due to the application of cutting-edge techniques such as CNN. As a well studied property for CNN-based models, the receptive field is a measurement f…
Image CategorizationDeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization
In recent years, the research landscape of machine learning in medical imaging has changed drastically from supervised to semi-, weakly- or unsupervised methods. This is mainly due to the fact that ground-truth labels ar…
ClusteringDeep ClusteringImage CategorizationCounterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Attention mechanism has demonstrated great potential in fine-grained visual recognition tasks. In this paper, we present a counterfactual attention learning method to learn more effective attention based on causal infere…
Causal InferencecounterfactualFew-Shot LearningFine-Grained Image Classification+7