… Accurate real-time object detection is … objects. To address these limitations, this paper
presents DART, an innovative automated end-to-end pipeline that revolutionizes object detection …

… be used for evaluating salient object detection models. We … to existing biased data sets and
opens new venues for future … issues specifically background clutter and number of objects. …

… The occupancy OS avoids these issues after rasterization. • The plausibility issue of point …
We also compare BtcDet with other models on the Waymo Open Dataset (WOD). We report …

… In contrast, our work delves into the intricacies of the Open Images dataset by addressing
the issues of implicit and explicit multi-labels, as well as the imbalance in label distribution. …

… Among them, the work by Viola and Jones [5], designed for general object detection, has
gained widespread acceptance due to the availability of an open source implementation [6]. …

… In particular, we discuss the issues of encoding and fitness evaluation. Section 6 presents
a brief review on SVMs. Our experimental results and comparisons using genetic eigenvector …

… QCNN is particularly interesting and promising for deep neural networks and could open
up … also solve present issues in the field of computer vision. This paper reviews various 3D …

… in the fields of object detection and classifier combination algo… Object Detection The object
detection systems that have been … , the reasons why they work so well is still open to debate. …

… in the industrial floor lines, such as vision, opened new horizons for the analytics tools for …
methods used for the quality control and issues of the manufacturing industry and just talks …

… Section 7 exposes open issues and the future research … object detector. It introduces a
semantic space built from the classes’ word embeddings and trains the detector to project object …