Generative Scatternet Hybrid Deep Learning (G-Shdl) Network with Structural Priors for Semantic Image Segmentation

Singh, Amarjot; Kingsbury, Nick

doi:10.1109/icassp.2018.8461542

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…The high-level kinship relation representational features of the faces, detected using MTCNN, are extracted using the proposed MSRHN network. The details of the proposed ScatterNet Hybrid Network, inspired from Singh et al's work in (Singh and Kingsbury 2017b,c;Singh, Hazarika, and Bhattacharya 2017;Singh and Kingsbury 2018), are explained in this section. This Hybrid network uses an Inception ResNet (IR) in the back-end and a handcrafted twolayered parametric log ScatterNet (Singh and Kingsbury 2017a) in the front-end, as shown in Fig.…”

Section: Memory Augmented Scatternet Resnet Hybrid (Msrhn) Networkmentioning

confidence: 99%

ChildrEN SafEty and Rescue (CENSER) System for Trafficked Children from Brothels in India

Hemadri¹,

Singh²,

Singh³

2022

AAAI

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Human child trafficking has become a global epidemic with over 10 million children forced into labor or prostitution. In this paper, we propose the ChildrEN SafEty and Rescue (CENSER) system used by the Guria non-profit organization to retrieve trafficked children from brothels in India. The CENSER system is formed of the proposed Memory Augmented ScatterNet ResNet Hybrid (MSRHN) network trained on three databases containing images of trafficked children at different ages, their kins, and their sketches. The CENSER system encodes the input image of a child using the proposed Memory Augmented ScatterNet ResNet Hybrid (MSRHN) network and queries the encoding with the (i) Age, (ii) Kinship, and (iii) Sketch databases to establish the child's identity. The CENSER system can also predict if a child is a minor, which is used along with their identity to convince law enforcement to initiate the rescue operation. The MSRHN network is pre-trained on the KinFace database and then fine-tuned on the three databases. The performance of the proposed model is compared with several state-of-the-art methods.

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Section: Memory Augmented Scatternet Resnet Hybrid (Msrhn) Networkmentioning

confidence: 99%

ChildrEN SafEty and Rescue (CENSER) System for Trafficked Children from Brothels in India

Hemadri¹,

Singh²,

Singh³

2022

AAAI

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“…This section details the proposed ScatterNet Hybrid Deep Learning (SHDL) network, inspired from Singh et al's work in [28,29,25,30], composed by combining the hand-crafted (front-end) two-layer parametric log Scat-terNet [27] with the regression network (RN) (back-end) shown in Fig. 3.…”

Section: Scatternet Hybrid Deep Learning Networkmentioning

confidence: 99%

Eye in the Sky: Real-Time Drone Surveillance System (DSS) for Violent Individuals Identification Using ScatterNet Hybrid Deep Learning Network

Singh

Patil

Omkar

2018

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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117

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Drone systems have been deployed by various law enforcement agencies to monitor hostiles, spy on foreign drug cartels, conduct border control operations, etc. This paper introduces a real-time drone surveillance system to identify violent individuals in public areas. The system first uses the Feature Pyramid Network to detect humans from aerial images. The image region with the human is used by the proposed ScatterNet Hybrid Deep Learning (SHDL) network for human pose estimation. The orientations between the limbs of the estimated pose are next used to identify the violent individuals. The proposed deep network can learn meaningful representations quickly using ScatterNet and structural priors with relatively fewer labeled examples. The system detects the violent individuals in real-time by processing the drone images in the cloud. This research also introduces the aerial violent individual dataset used for training the deep network which hopefully may encourage researchers interested in using deep learning for aerial surveillance. The pose estimation and violent individuals identification performance is compared with the state-ofthe-art techniques.

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Generative Scatternet Hybrid Deep Learning (G-Shdl) Network with Structural Priors for Semantic Image Segmentation

Cited by 2 publications

References 21 publications

ChildrEN SafEty and Rescue (CENSER) System for Trafficked Children from Brothels in India

ChildrEN SafEty and Rescue (CENSER) System for Trafficked Children from Brothels in India

Eye in the Sky: Real-Time Drone Surveillance System (DSS) for Violent Individuals Identification Using ScatterNet Hybrid Deep Learning Network

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