JavaShuo
欄目
標籤
diagnosing error in object detectors 淺析
時間 2021-01-16
原文
原文鏈接
目標檢測器中的誤差診斷 誤差來源: [1] localization error (定位誤差) [2] confusion with similar objects (相似目標混淆) [3] confusion with dissimilar objects (非相似目標混淆) [4] confusion with background (背景混淆) [5] object size (目標尺寸)
>>阅读原文<<
相關文章
1.
one-stage object detectors(1)
2.
MaxPool NMS Getting rid of NMS bottlenecks in Two-Stage Object Detectors
3.
ScratchDet: Exploring to train single-shot object detectors from scratch
4.
Bounding box object detectors: understanding YOLO, You Only Look Once
5.
Reading Note: DSOD: Learning Deeply Supervised Object Detectors from Scratch
6.
Training Region-based Object Detectors with Online Hard Example Mining
7.
Object源碼淺析
8.
《Adapting Object Detectors via Selective Cross-Domain Alignment》筆記
9.
DSOD: Learning Deeply Supervised Object Detectors from Scratch
10.
Speed/accuracy trade-offs for modern convolutional object detectors
更多相關文章...
•
ADO Error 對象
-
ADO 教程
•
SQL IN 操作符
-
SQL 教程
•
RxJava操作符(五)Error Handling
•
互聯網組織的未來:剖析GitHub員工的任性之源
相關標籤/搜索
diagnosing
detectors
object...object
error
object
淺析
J2EE淺析
源碼淺析
淺淺
MyBatis教程
Hibernate教程
0
分享到微博
分享到微信
分享到QQ
每日一句
每一个你不满意的现在,都有一个你没有努力的曾经。
最新文章
1.
Appium入門
2.
Spring WebFlux 源碼分析(2)-Netty 服務器啓動服務流程 --TBD
3.
wxpython入門第六步(高級組件)
4.
CentOS7.5安裝SVN和可視化管理工具iF.SVNAdmin
5.
jedis 3.0.1中JedisPoolConfig對象缺少setMaxIdle、setMaxWaitMillis等方法,問題記錄
6.
一步一圖一代碼,一定要讓你真正徹底明白紅黑樹
7.
2018-04-12—(重點)源碼角度分析Handler運行原理
8.
Spring AOP源碼詳細解析
9.
Spring Cloud(1)
10.
python簡單爬去油價信息發送到公衆號
本站公眾號
歡迎關注本站公眾號,獲取更多信息
相關文章
1.
one-stage object detectors(1)
2.
MaxPool NMS Getting rid of NMS bottlenecks in Two-Stage Object Detectors
3.
ScratchDet: Exploring to train single-shot object detectors from scratch
4.
Bounding box object detectors: understanding YOLO, You Only Look Once
5.
Reading Note: DSOD: Learning Deeply Supervised Object Detectors from Scratch
6.
Training Region-based Object Detectors with Online Hard Example Mining
7.
Object源碼淺析
8.
《Adapting Object Detectors via Selective Cross-Domain Alignment》筆記
9.
DSOD: Learning Deeply Supervised Object Detectors from Scratch
10.
Speed/accuracy trade-offs for modern convolutional object detectors
>>更多相關文章<<