most citedFlower Categorization using Deep Convolutional Neural Networks

21 citations · 27 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2018

ViS-HuD: Using Visual Saliency to Improve Human Detection with Convolutional Neural Networks

Vandit Gajjar, Yash Khandhediya, Ayesha Gurnani +2

The paper presents a technique to improve human detection in still images using deep learning. Our novel method, ViS-HuD, computes visual saliency map from the image. Then the inpu…

cs.CV2018

SAF- BAGE: Salient Approach for Facial Soft-Biometric Classification - Age, Gender, and Facial Expression

Ayesha Gurnani, Kenil Shah, Vandit Gajjar +2

How can we improve the facial soft-biometric classification with help of the human visual system? This paper explores the use of saliency which is equivalent to the human visual sy…

cs.CV20173 cited

Human Detection and Tracking for Video Surveillance A Cognitive Science Approach

Vandit Gajjar, Ayesha Gurnani, Yash Khandhediya

With crimes on the rise all around the world, video surveillance is becoming more important day by day. Due to the lack of human resources to monitor this increasing number of came…

cs.CV201721 cited

Flower Categorization using Deep Convolutional Neural Networks

Ayesha Gurnani, Viraj Mavani, Vandit Gajjar +1

We have developed a deep learning network for classification of different flowers. For this, we have used Visual Geometry Group's 102 category flower dataset having 8189 images of…

cs.CV20173 cited

A Novel Approach for Image Segmentation based on Histograms computed from Hue-data

Viraj Mavani, Ayesha Gurnani, Jhanvi Shah

Computer Vision is growing day by day in terms of user specific applications. The first step of any such application is segmenting an image. In this paper, we propose a novel and g…