Dataset issues in object recognition by Ponce, J, Berg, TL, Everingham, M, Forsyth, DA, Hebert, M, Lazebnik, S, Marszalek, M, Schmid, C, Russell, BC, Torralba, A, Williams, CKI, Zhang, J, Zisserman, A

“…Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. …”

Canonical frames for planar object recognition by Rothwell, CA, Zisserman, A, Forsyth, DA, Mundy, JL

Place recognition using line-junction-lines in urban environments by Tang, Xiaoyu, Fu, Wenhao, Jiang, Muyun, Peng, Guohao, Wu, Zhenyu, Yue, Yufeng, Wang, Danwei

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Visual place recognition for autonomous robots using deep learning by Huang, Yifeng

“…Visual place recognition has become a challenging and attractive field in computer vision and robotics because it involves many methods to recognize the appearance of natural scenes that may be different. …”
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Open-RadVLAD: fast and robust radar place recognition by Gadd, M, Newman, P

“…Radar place recognition often involves encoding a live scan as a vector and matching this vector to a database in order to recognise that the vehicle is in a location that it has visited before. …”

Hybrid SLAM and object recognition on an embedded platform by Low, Timothy Zhi Hao

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Object recognition using deep learning features by Zhu, Daiqing

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3D object recognition using invariance by Zisserman, A, Forsyth, D, Mundy, J, Rothwell, C, Liu, J, Pillow, N

“…<p>The systems and concepts described in this paper document the evolution of the geometric invariance approach to object recognition over the last five years. Invariance overcomes one of the fundamental difficulties in recognising objects from images: that the appearance of an object depends on viewpoint. …”

Extreme learning machine based fast object recognition by Xu, Jiantao, Zhou, Hongming, Huang, Guang-Bin

“…This paper further studies the performance of ELM and its variants in object recognition using two different feature extraction methods. …”
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Small object recognition using machine learning techniques by Loy, Hui Juan

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Object recognition and pose estimation in robotic grasping system by Zhou, Jiadong

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ConvNet-based visual place recognition under appearance changes for unmanned vehicles by Li, Heshan

“…As a VPR(visual place recognition problem), the goal is to retrieve the correct reference frames in database which depict the same place as given query image.For retrieval-basedVPR, methods can be classified as VLAD-based and sum-based. …”
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Point cloud based place recognition and localization for autonomous robots using deep learning by Fang, Shu

“…Most of the researchers focus on putting forward 2D-images-based place recognition and localization algorithms, few researchers pay attention to letting robots use point cloud to perform localization work, due to the difficulty of extracting point cloud's local features, which can be transformed into global descriptors. …”
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Designing a spiking neural network system for object recognition by Thong, Jing Yuan

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Place recognition for unmanned vehicle based on 3D LiDAR and semantic point cloud by Zhao, Yangyang

“…Place recognition is an important task in the computer vision and robotics communities, with a wild application in many fields. …”
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PRFusion: toward effective and robust multi-modal place recognition with image and point cloud fusion by Wang, Sijie, Kang, Qiyu, She, Rui, Zhao, Kai, Song, Yang, Tay, Wee Peng

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Face/object recognition and tracking on IoT device with 3D camera by Lin, Yuxin

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SectionKey: 3-D semantic point cloud descriptor for place recognition in large-scale environments by Jin, Shutong

“…Place recognition is seen as a crucial factor to correct cumulative errors in Simultaneous Localization and Mapping (SLAM) applications. …”
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ViObject: Harness Passive Vibrations for Daily Object Recognition with Commodity Smartwatches by Chen, Wenqiang, Lin, Shupei, Peng, Zhencan, Parizi, Farshid Salemi, Heo, Seongkook, Patel, Shwetak, Matusik, Wojciech, Zhao, Wei, Stankovic, John

“…This paper presents a novel system, ViObject, for passive object recognition that uses accelerometer and gyroscope sensor data from commodity smartwatches to identify untagged everyday objects. …”
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Generic Object Recognition with Local Receptive Fields Based Extreme Learning Machine by Bai, Zuo, Kasun, Liyanaarachchi Lekamalage Chamara, Huang, Guang-Bin

Subjects: “…Generic object recognition; local receptive fields; Extreme Learning Machine (ELM)…”
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