Computer Science > Computer Vision and Pattern Recognition
[Submitted on 17 Mar 2020 (v1), last revised 11 Nov 2020 (this version, v4)]
Title:Real Time Multi-Class Object Detection and Recognition Using Vision Augmentation Algorithm
View PDFAbstract:The aim of this research is to detect small objects with low resolution and noise. The existing real time object detection algorithm is based on the deep neural network of convolution need to perform multilevel convolution and pooling operations on the entire image to extract a deep semantic characteristic of the image. The detection models perform better for large objects. The features of existing models do not fully represent the essential features of small objects after repeated convolution operations. We have introduced a novel real time detection algorithm which employs upsampling and skip connection to extract multiscale features at different convolution levels in a learning task resulting a remarkable performance in detecting small objects. The detection precision of the model is shown to be higher and faster than that of the state-of-the-art models.
Submission history
From: Al-Akhir Nayan [view email][v1] Tue, 17 Mar 2020 01:08:24 UTC (593 KB)
[v2] Tue, 14 Apr 2020 00:42:06 UTC (608 KB)
[v3] Mon, 18 May 2020 06:32:23 UTC (1 KB) (withdrawn)
[v4] Wed, 11 Nov 2020 18:22:22 UTC (1,523 KB)
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