IEEE

Machine Learning Assisted Characterization of Hidden Metallic Objects

Abstract: This letter introduces a new method for magnetic polarizability tensor measurement using a pulse induction metal detector and electromagnetic tracking. Machine learning-based object depth ...
IEEE

Few-Shot Class-Incremental Learning for Classification and Object Detection: A Survey

Abstract: Few-shot Class-Incremental Learning (FSCIL) presents a unique challenge in Machine Learning (ML), as it necessitates the Incremental Learning (IL) of new classes from sparsely labeled ...
Scientific Research Publishing

Traffic Object Detection Using YOLOv12 ()

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...
Frontiers

A machine learning-based detection, classification, and quantification of marine litter along the central east coast of India

Globally, the growth of plastic production has increased exponentially from 1.5 million metric tons (Mt) in 1950 to 400.3 Mt in 2022, resulting in a substantial increase of marine litter along the ...
Frontiers

YOLOPears: a novel benchmark of YOLO object detectors for multi-class pear surface defect detection in quality grading systems

Pears are one of the most widely consumed fruits, and their quality directly impacts consumer satisfaction. Surface defects, such as black spots and minor blemishes, are crucial indicators of pear ...
marktechpost

LLMDet: How Large Language Models Enhance Open-Vocabulary Object Detection

Open-vocabulary object detection (OVD) aims to detect arbitrary objects with user-provided text labels. Although recent progress has enhanced zero-shot detection ability, current techniques handicap ...