Classification and Localization of Naval Mines With Superellipse Active Contours
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Journal of Oceanic Engineering"
DOI: 10.1109/joe.2018.2835218
Abstract: In this paper, an approach for the classification and localization of geometric shapes, e.g., man-made objects or different types of geological features, in sonar images is presented. It is applied to a concrete application case,… read more here.
Keywords: classification localization; active contours; step; image ... See more keywords
CrabNet: Fully Task-Specific Feature Learning for One-Stage Object Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3162099
Abstract: Object detection is usually solved by learning a deep architecture involving classification and localization tasks, where feature learning for these two tasks is shared using the same backbone model. Recent works have shown that suitable… read more here.
Keywords: feature; task specific; detection; object detection ... See more keywords
Go Deep or Broad? Exploit Hybrid Network Architecture for Weakly Supervised Object Classification and Localization.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3225180
Abstract: Weakly supervised object classification and localization are learned object classes and locations using only image-level labels, as opposed to bounding box annotations. Conventional deep convolutional neural network (CNN)-based methods activate the most discriminate part of… read more here.
Keywords: network; weakly supervised; classification; hybrid network ... See more keywords
Biomarker-Based Classification and Localization of Renal Lesions Using Learned Representations of Histology—A Machine Learning Approach to Histopathology
Sign Up to like & getrecommendations! Published in 2021 at "Toxicologic Pathology"
DOI: 10.1177/0192623320987202
Abstract: Several deep learning approaches have been proposed to address the challenges in computational pathology by learning structural details in an unbiased way. Transfer learning allows starting from a learned representation of a pretrained model to… read more here.
Keywords: classification localization; learned representations; biomarker; histopathology ... See more keywords