Frontiers

Self-supervised transfer learning for few-shot classification on marine plankton images

The classification of marine plankton images is of great significance in ecological studies and environmental monitoring. In practical applications, plankton image classification faces several ...
Frontiers

Semi-supervised segmentation of forest fires from UAV remote sensing images via panoramic feature fusion and pixel contrastive learning

1 School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China 2 College of Information Science and Technology, Nanjing Forestry University, Nanjing, China ...
Optics

Optimizing deployment costs of inspection functions with Inference Deep Learning Licenses.

Euresys announce the availability of Cost-Effective Inference Licenses for image classification, supervised or unsupervised segmentation and object localization. When implementing Deep Learning on ...
GitHub

microCLIP: Unsupervised CLIP Adaptation via Coarse-Fine Token Fusion for Fine-Grained Image Classification

microCLIP is a lightweight self-training framework that adapts CLIP for fine-grained image classification without requiring labeled data. While CLIP is strong in zero-shot transfer, it primarily ...
Scientific Research Publishing

Xie, Y., Zhang, J. and Xia, Y. (2019) Semi-Supervised Adversarial Model for Benign-Malignant Lung Nodule Classification on Chest CT. Medical Image Analysis, 57, 237-248.

ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...
IEEE

Unsupervised, Untrained and Robust Single Image Superpixel Segmentation Network

Abstract: Image superpixel segmentation has greatly benefited from the excellent feature extraction capabilities of neural networks. However, most existing neural network-based superpixel segmentation ...
EurekAlert!

Unsupervised cross-domain adaptation: single-pixel image transmission in unknown dynamic channels

Imaging technologies are ubiquitous in our daily lives, from smartphone cameras to medical imaging devices, helping us capture images and perceive objects. However, when faced with complex ...
C&EN

Unsupervised Machine Learning-Based Image Recognition of Raw Infrared Spectra: Toward Chemist-like Chemical Structural Classification and Beyond Numerical Data

Faculty of Advanced Engineering, Tokyo University of Science, Tokyo 125-8585, Japan ...