The phrase "approaches for object" is not correct and lacks clarity in written English.
It may be intended to refer to methods or strategies related to a specific object, but it needs more context to be usable.
Example: "We need to discuss the various approaches for object recognition in our project."
Alternatives: "methods for object" or "strategies for object".
Most conventional approaches for object detection are background subtraction, optical flow and spatio-temporal filtering method.
In this research, particle filter is selected as the tracking framework among the common approaches for object tracking.
Approaches for object tracking can be categorized into three groups: point tracking, kernel tracking, and silhouette tracking [5].
Several research groups have recently shown that CNNs outperform classical approaches for object classification or detection that are based on hand-crafted features [8, 24].
For that reason, approaches for object detection that are simply using occlusion detectors will not be able to gain the full object outline.
Like the conventional clustering approaches for objects, the attributes within the same cluster are expected to possess high similarity, but within different clusters possess low similarity.
Radio frequency identification (RFID) provides a non-line-of-sight (NLOS) and contactless approach for object identification.
For our application, we employed HOG feature extraction since it is known to be a robust approach for object detection.
A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed.
Experiments were conducted to test this approach for object recognition with benchmark datasets under two scenarios: (1) source and target contains labeled training instances for all categories and (2) source contains labeled training instances for all categories but the target only contains half of the categories and shall be tested with data containing all categories.
To solve these problems, we proposed a new method that incorporates the use of a revised physically based (RPB) model to correct both atmospheric and terrain-caused illumination effects on Landsat images, an improved vegetation index (VI -based technique for estimating the FVI -basedn adaptechnique shiforapproach for objestimatingFVC segmentheion.
