Current top performing object detectors employ detection proposals to guide the search for objects, thereby avoiding exhaustive sliding window search across images. Despite the popularity and widespread use of detection proposals, it is unclear which trade-offs are made when using them during object detection. We provide an in-depth analysis of twelve proposal methods along with four baselines regarding proposal repeatability, ground truth annotation recall on PASCAL, ImageNet, and MS COCO, and their impact on DPM, R-CNN, and Fast R-CNN detection performance. Our analysis shows that for object detection improving proposal localisation accuracy is as important as improving recall. We introduce a novel metric, the average recall (AR), which rewards both high recall and good localisation and correlates surprisingly well with detection performance. Our findings show common strengths and weaknesses of existing methods, and provide insights and metrics for selecting and tuning proposal methods.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/TPAMI.2015.2465908 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Weight loss therapy and addiction: increased risk after bariatric surgery but reduced risk with GLP-1 receptor agonists.
Diabetes Metab
January 2025
Division of Diabetes, Nutrition and Metabolic Disorders, CHU Liège, Liège, Belgium; Division of Clinical Pharmacology, Centre for Interdisciplinary Research on Medicines (CIRM), Liège University, Liège, Belgium. Electronic address:
Background: Obesity is an increasing public health problem because of its high prevalence and associated morbidity and mortality. Two weight-loss strategies are currently used, either bariatric surgery or pharmacological therapy with glucagon-like peptide-1 receptor agonists (GLP-1RAs). Preclinical studies in rodents suggested an increased risk of additive disorders after bariatric surgery contrasting with a reduced risk with GLP-1RAs.
View Article and Find Full Text PDFUrological injuries complicating pregnancy-related hysterectomy: Analysis of risk factors and proposal to improve the quality of care.
Eur J Obstet Gynecol Reprod Biol
January 2025
Obstetrics Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Purpose: While strategies aimed at preventing urological injuries complicating hysterectomy for gynaecological indications and placenta accreta surgery have been proposed, a comprehensive model for pregnancy-related hysterectomy (PRH) is lacking. The aim of this study was to investigate risk factors for urological complications of obstetric hysterectomy, and to propose strategies to improve the quality of care.
Methods: This retrospective study of patients undergoing PRH was conducted in an academic centre between 2009 and 2022.
Rapid on-site determination of heavy metals and metalloids in contaminated biochar samples by accelerated leaching process coupled with voltammetric sensors.
Talanta
January 2025
Residues and Resource Reclamation Centre (R3C), Nanyang Environment and Water Research Institute, Nanyang Technological University, 1 Cleantech Loop, CleanTech One, 637141, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore. Electronic address:
Heavy metals and metalloids are the most common environmental pollutants. Toxicity characteristic leaching procedure (TCLP) is a standard operating procedure that is used to assess heavy metal and metalloid compositions, and evaluate the hazardous nature of waste and waste-derived materials for reuse or disposal, such as determining landfill suitability. However, TCLP and the following detections are time-consuming and require bulky laboratory-based instruments and trained personnel.
View Article and Find Full Text PDFAutomated ultrasonography of hepatocellular carcinoma using discrete wavelet transform based deep-learning neural network.
Med Image Anal
January 2025
Department of Electrical and Computer Engineering, College of Information and Communication Engineering, Sungkyunkwan University, Suwon, 440-746, South Korea. Electronic address:
This study introduces HCC-Net, a novel wavelet-based approach for the accurate diagnosis of hepatocellular carcinoma (HCC) from abdominal ultrasound (US) images using artificial neural networks. The HCC-Net integrates the discrete wavelet transform (DWT) to decompose US images into four sub-band images, a lesion detector for hierarchical lesion localization, and a pattern-augmented classifier for generating pattern-enhanced lesion images and subsequent classification. The lesion detection uses a hierarchical coarse-to-fine approach to minimize missed lesions.
View Article and Find Full Text PDFChange surface regression for nonlinear subgroup identification with application to warfarin pharmacogenomics data.
Biometrics
January 2025
Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Singapore.
Pharmacogenomics stands as a pivotal driver toward personalized medicine, aiming to optimize drug efficacy while minimizing adverse effects by uncovering the impact of genetic variations on inter-individual outcome variability. Despite its promise, the intricate landscape of drug metabolism introduces complexity, where the correlation between drug response and genes can be shaped by numerous nongenetic factors, often exhibiting heterogeneity across diverse subpopulations. This challenge is particularly pronounced in datasets such as the International Warfarin Pharmacogenetic Consortium (IWPC), which encompasses diverse patient information from multiple nations.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!