Object detectionActive learning (AL) for object detection (OD) aims to reduce labeling costs by selecting the most valuable samples that enhance the detection network from the unlabeled pool. Due to the complex
Detecting and locating objects is one of the most common uses of deep learning for computer vision. Applications include helping autonomous systems navigate complex environments, locating medical conditions like tumors, and identifying ready-to-harvest c
Active Learning for Deep Object DetectionClemens-Alexander Brust 1 , Christoph Käding 1,2 and Joachim Denzler 1,21 Computer Vision Group, Friedrich Schiller University Jena, Germany2 Michael Stifel Center Jena, Germany{f author, s author}@uni-jena.deKeywords: Active Learning, Deep Learning, ...
【目标检测系列:一】综述阅读笔记 Deep Learning for Generic Object Detection: A Survey,程序员大本营,技术文章内容聚合第一站。
Deep learning is one potential solution for object detection and scene perception problems, which can enable algorithm-driven and data-driven cars. In this article, we aim to bridge the gap between deep learning and self-driving cars through a comprehensive survey. We begin with an introduction ...
With the development of CNN, deep active learning for object detection has been extensively studied. The uncertainty-based methods are widely used for querying samples. Feng et al. [33] use MC dropout and Deep Ensembles to obtain uncertainty estimations and select the most uncertain samples by ...
Object Recognition Object vision Artificial Intelligence 1Introduction As a longstanding, fundamental and challenging problem in computer vision, object detection (illustrated in Fig.1) has been an active area of research for several decades (Fischler and Elschlager1973). The goal of object detection ...
Machine Learning Object Recognition Object vision Artificial Intelligence 1 Introduction As a longstanding, fundamental and challenging problem in computer vision, object detection (illustrated in Fig. 1) has been an active area of research for several decades (Fischler and Elschlager 1973). The...
接下来，我需要考虑Agentic Object Detection可能的实现原理。可能有以下几个组成部分：1. **主动感知（Active Perception）**：智能体主动调整传感器参数（如摄像头角度、焦距）或选择不同的视角来优化检测结果。例如，如果检测到某个物体但置信度低，智能体可能会移动摄像头以获取更好的视角。2. **强化学习（...
train_ssd_gmm_supervised_learning.py Initial commit Oct 13, 2021 View all files README License This repository is the official PyTorch implementation ofActive Learning for Deep Object Detection via Probabilistic Modeling, ICCV 2021. The proposed method is implemented based on theSSD pytorch. ...