A state-of-the-art review on mobile robotics tasks using artificial intelligence and visual data
Nowadays, the field of mobile robotics has experienced an important evolution and these
robots are more commonly proposed to solve different tasks autonomously. The use of …
robots are more commonly proposed to solve different tasks autonomously. The use of …
[HTML][HTML] A role of computer vision in fruits and vegetables among various horticulture products of agriculture fields: A survey
MK Tripathi, DD Maktedar - Information Processing in Agriculture, 2020 - Elsevier
Computer vision is a consistent and advanced technique for image processing, with the
propitious outcome, and enormous potential. A computer vision has been strongly adopted …
propitious outcome, and enormous potential. A computer vision has been strongly adopted …
Approximating cnns with bag-of-local-features models works surprisingly well on imagenet
Deep Neural Networks (DNNs) excel on many complex perceptual tasks but it has proven
notoriously difficult to understand how they reach their decisions. We here introduce a high …
notoriously difficult to understand how they reach their decisions. We here introduce a high …
Understanding bag-of-words model: a statistical framework
The bag-of-words model is one of the most popular representation methods for object
categorization. The key idea is to quantize each extracted key point into one of visual words …
categorization. The key idea is to quantize each extracted key point into one of visual words …
Locality-constrained linear coding for image classification
The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers
to achieve good image classification performance. This paper presents a simple but effective …
to achieve good image classification performance. This paper presents a simple but effective …
[图书][B] Decision forests for computer vision and medical image analysis
A Criminisi, J Shotton - 2013 - books.google.com
Decision forests (also known as random forests) are an indispensable tool for automatic
image analysis. This practical and easy-to-follow text explores the theoretical underpinnings …
image analysis. This practical and easy-to-follow text explores the theoretical underpinnings …
Linear spatial pyramid matching using sparse coding for image classification
Recently SVMs using spatial pyramid matching (SPM) kernel have been highly successful in
image classification. Despite its popularity, these nonlinear SVMs have a complexity O (n …
image classification. Despite its popularity, these nonlinear SVMs have a complexity O (n …
PCA-SIFT: A more distinctive representation for local image descriptors
Y Ke, R Sukthankar - Proceedings of the 2004 IEEE Computer …, 2004 - ieeexplore.ieee.org
Stable local feature detection and representation is a fundamental component of many
image registration and object recognition algorithms. Mikolajczyk and Schmid (June 2003) …
image registration and object recognition algorithms. Mikolajczyk and Schmid (June 2003) …
Evaluation of local spatio-temporal features for action recognition
Local space-time features have recently become a popular video representation for action
recognition. Several methods for feature localization and description have been proposed in …
recognition. Several methods for feature localization and description have been proposed in …
Appearance-only SLAM at large scale with FAB-MAP 2.0
We describe a new formulation of appearance-only SLAM suitable for very large scale place
recognition. The system navigates in the space of appearance, assigning each new …
recognition. The system navigates in the space of appearance, assigning each new …