An Artificial Neural Network for Image Classification Inspired by the Aversive Olfactory Learning Neural Circuit in Caenorhabditis elegans
Sign Up to like & getrecommendations! Published in 2024 at "Advanced Science"
DOI: 10.1002/advs.202410637
Abstract: This study introduces an artificial neural network (ANN) for image classification task, inspired by the aversive olfactory learning neural circuit in Caenorhabditis elegans (C. elegans). Although artificial neural networks (ANNs) have demonstrated remarkable performance in… read more here.
Keywords: classification; olfactory learning; image classification; aversive olfactory ... See more keywords
Pneumonia Image Classification Based on Lightweight Mobile ViT Networks
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.70153
Abstract: Pneumonia is a common respiratory disease, and accurate image classification is crucial for early diagnosis and treatment. However, traditional deep learning models limit their application in the field of medical image processing due to their… read more here.
Keywords: classification; image classification; image; mobile vit ... See more keywords
SF Net: A Pyramid‐Based Feature Fusion Convolutional Neural Network With Embedded Squeeze‐and‐Excitation Mechanism for Retinal OCT Image Classification
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.70197
Abstract: Age‐related macular degeneration (AMD) and diabetic macular edema (DME) are among the leading causes of blindness worldwide, and optical coherence tomography (OCT) analysis plays a crucial role in diagnosing and treating ocular diseases. While deep… read more here.
Keywords: classification; image classification; squeeze excitation; image ... See more keywords
Semisupervised image classification by mutual learning of multiple self‐supervised models
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22814
Abstract: Image classification has been widely adopted by current social media applications. Compared with fully supervised classification, semisupervised classification attracts more attention because it is commonly observed that category labels are only available for a small… read more here.
Keywords: self supervised; image classification; image; mutual learning ... See more keywords
Convolutional‐capsule network for gastrointestinal endoscopy image classification
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22815
Abstract: Automated diagnosis of digestive tract diseases from gastrointestinal endoscopy images is of high importance for improving the diagnosis accuracy and efficiency. The current mainstream methods for image classification of digestive tract endoscopy images are based… read more here.
Keywords: network; classification; gastrointestinal endoscopy; image classification ... See more keywords
FaxMatch: Multi-Curriculum Pseudo-Labeling for Semi-supervised Medical Image Classification.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16312
Abstract: BACKGROUND Semi-supervised learning (SSL) can effectively use information from unlabeled data to improve model performance, which has great significance in medical imaging tasks. Pseudo-labeling is a classical SSL method that uses a model to predict… read more here.
Keywords: semi supervised; pseudo labeling; medical image; pseudo ... See more keywords
Economical crowdsourcing for camera trap image classification
Sign Up to like & getrecommendations! Published in 2018 at "Remote Sensing in Ecology and Conservation"
DOI: 10.1002/rse2.84
Abstract: Camera trapping is widely used to monitor mammalian wildlife but creates large image datasets that must be classified. In response, there is a trend towards crowdsourcing image classification. For high‐profile studies of charismatic faunas, many… read more here.
Keywords: image; classification; camera trap; consensus ... See more keywords
Feasibility of improving vocal fold pathology image classification with synthetic images generated by DDPM-based GenAI: a pilot study
Sign Up to like & getrecommendations! Published in 2025 at "European Archives of Oto-Rhino-Laryngology"
DOI: 10.1007/s00405-025-09443-4
Abstract: Voice disorders (VD) are often linked to vocal fold structural pathologies (VFSP). Laryngeal imaging plays a vital role in assessing VFSPs and VD in clinical and research settings, but challenges like scarce and imbalanced datasets… read more here.
Keywords: classification; feasibility improving; image classification; synthetic images ... See more keywords
Research on image classification method based on convolutional neural network
Sign Up to like & getrecommendations! Published in 2020 at "Neural Computing and Applications"
DOI: 10.1007/s00521-020-04930-7
Abstract: Image classification method is currently the more popular image technology, but it still has certain problems in practice. In order to improve the image classification effect, this study proposes a new convolution kernel, which can… read more here.
Keywords: image classification; image; classification method; network ... See more keywords
On measuring and employing texture directionality for image classification
Sign Up to like & getrecommendations! Published in 2021 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-021-01013-8
Abstract: Directionality is useful in many computer vision, pattern recognition, visualization, and multimedia applications since it is considered as an important pre-attentive attribute in human vision. To support using directionality (i.e., orientedness) for texture discrimination, a… read more here.
Keywords: element; texture directionality; measure; image classification ... See more keywords
A review of hyperspectral image classification based on graph neural networks
Sign Up to like & getrecommendations! Published in 2025 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-025-11169-y
Abstract: Hyperspectral images provide rich spectral-spatial information but pose significant classification challenges due to high dimensionality, noise, mixed pixels, and limited labeled samples. Graph Neural Networks (GNNs) have emerged as a promising solution, offering a semi-supervised… read more here.
Keywords: classification; image classification; hyperspectral image; graph neural ... See more keywords