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20182021
most citedAbsolute distance prediction based on deep learning object detection and monocular depth estimation models

41 citations · 75 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.CV202141 cited

Absolute distance prediction based on deep learning object detection and monocular depth estimation models

Armin Masoumian, David G. F. Marei, Saddam Abdulwahab +3

Determining the distance between the objects in a scene and the camera sensor from 2D images is feasible by estimating depth images using stereo cameras or 3D cameras. The outcome…

cs.CV20192 cited

Hierarchical approach to classify food scenes in egocentric photo-streams

Estefania Talavera, Maria Leyva-Vallina, Md. Mostafa Kamal Sarker +3

Recent studies have shown that the environment where people eat can affect their nutritional behaviour. In this work, we provide automatic tools for a personalised analysis of a pe…

cs.CV2018

Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural Network

Vivek Kumar Singh, Hatem A. Rashwan, Santiago Romani +8

Mammogram inspection in search of breast tumors is a tough assignment that radiologists must carry out frequently. Therefore, image analysis methods are needed for the detection an…

cs.CV2018

MACNet: Multi-scale Atrous Convolution Networks for Food Places Classification in Egocentric Photo-streams

Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Estefania Talavera +3

First-person (wearable) camera continually captures unscripted interactions of the camera user with objects, people, and scenes reflecting his personal and relational tendencies. O…

cs.CV2018

Retinal Optic Disc Segmentation using Conditional Generative Adversarial Network

Vivek Kumar Singh, Hatem Rashwan, Farhan Akram +7

This paper proposed a retinal image segmentation method based on conditional Generative Adversarial Network (cGAN) to segment optic disc. The proposed model consists of two success…

cs.CV2018

Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification

Vivek Kumar Singh, Santiago Romani, Hatem A. Rashwan +9

This paper proposes a novel approach based on conditional Generative Adversarial Networks (cGAN) for breast mass segmentation in mammography. We hypothesized that the cGAN structur…