Efficacy Determination of Various Base Networks in Single Shot Detector for Automatic Mask Localisation in a Post COVID Setup

Jee, Gaurav; Harshvardhan, GM; Gourisaria, Mahendra Kumar; Singh, Vijander; Rautaray, Siddharth Swarup; Pandey, Manjusha

doi:10.1080/0952813x.2021.1960638

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…Figure 1. Architecture of SSD MobileNet V2 [20] MobileNet V2 model is an enhancement compared to MobileNet V1. By including shortcut connections (residual connection) and utilizing depth separable convolution, MobileNet V2 may more effectively minimize the number of weights and biases in network and will increase speed of operation [21].…”

Section: Ssd Mobilenet V2mentioning

confidence: 99%

“…Therefore, SSD is a very effective object detection technique for an input image and can detect a variety of object sizes because the output is directly linked to various numbers of convolutional layers. For each bounding box predicated in the output, a confidence score is provided for the label prediction and the predicted bounding box is taken in which having the highest value of confidence [20], [23]. SSD MobileNet V2 is pre-trained on the common objects in context (COCO) dataset to classify and detect several objects under complex conditions.…”

Section: Ssd Mobilenet V2mentioning

confidence: 99%

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Intelligence feeder system for stray cats

Saadoon,

Koyuncu

2023

IJEECS

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<span>Recently, <span lang="EN-US">the care of stray cats has become an important matter, given the difficulty for these animals to obtain food or water, whether in wild or remote areas, and this may cause the death of these animals. The aim of this work is to design and implement a low-cost feeding system for feral and indoor cats. The system is controlled by a jetson nano and arduino mega 2,560. The cat detection feeder system is built using the single shot multibox detector (SSD) MobileNet V2 algorithm. The system provides food and water for the cats. The SSD on jetson nano is implemented in real time. Jetson nano takes a picture using a webcam then runs the SSD algorithm. When a cat is detected, the arduino turns on a servo motor and a water pump. The system also includes a sim800l and GPS NEO-6M modules to send an alert message when the food and water tanks are empty. The message also contains the location of the feeder. When testing the system to determine the effectiveness of the functions, the SSD algorithm succeeded in recognizing cats, the system successfully provided food for the cats, and all parts of the device worked in high harmonic.</span></span>

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Section: Ssd Mobilenet V2mentioning

confidence: 99%

Section: Ssd Mobilenet V2mentioning

confidence: 99%

Intelligence feeder system for stray cats

Saadoon,

Koyuncu

2023

IJEECS

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Detection of Autism Spectrum Disorder Through Orthogonal Decomposition and Pearson Correlation for Feature Selection

Jee

Chouhan

Gourisaria

et al. 2022

2021 4th International Conference on Recent Trends in Computer Science and Technology (ICRTCST)

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Recognition of Brazilian vertical traffic signs and lights from a car using Single Shot Multi box Detector

Pierre,

Fernandes

2024

JBCS

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This work presents an automated system for recognizing Brazilian vertical traffic signs and lights using artificial intelligence. The main objective of the system is to contribute to road safety by alerting drivers to potential risks such as speeding, alcohol consumption, and cell phone use, which could lead to severe accidents. The system’s core contribution lies in its ability to accurately recognize various traffic signs and lights, providing crucial warnings to drivers. To achieve this, the system utilizes a light version of the single shot multi box detector as its detection algorithm and experiments with three Mobilenet versions as base networks. The optimal Mobilenet version is selected based on a mean average precision higher than 80%, which guarantees reliable detection results. The dataset used for training and evaluation comprises images extracted from YouTube traffic videos, each annotated to create the necessary labels for training. Through this extensive experimentation, the system demonstrates its efficacy in achieving accurate and efficient detection. The results of the experiments are compared with other existing approaches and our work significantly advances the field by providing a tailored dataset, an optimized model, and also valuable insights into traffic sign and light recognition, collectively contributing to the improvement of road safety.

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Efficacy Determination of Various Base Networks in Single Shot Detector for Automatic Mask Localisation in a Post COVID Setup

Cited by 3 publications

References 35 publications

Intelligence feeder system for stray cats

Intelligence feeder system for stray cats

Detection of Autism Spectrum Disorder Through Orthogonal Decomposition and Pearson Correlation for Feature Selection

Recognition of Brazilian vertical traffic signs and lights from a car using Single Shot Multi box Detector

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