Small Object Detection From Video and Classification Using Deep Learning

Arthi, R.; Ahuja, Jai; Kumar, Sachin; Thakur, Pushpendra; Sharma, Tanay

doi:10.1007/978-981-15-8685-9_10

Cited by 6 publications

(2 citation statements)

References 6 publications

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“…Arthi et al explained about various segmentation and detection classification model [14]. Alhassan and Zainon used a modern learning-based technique to process automatic the Bat Algorithm with Fuzzy C-Ordered Means (BAFCOM) clustering algorithm advocated segmenting the tumour and developed a Five-step based algorithm for detection and feature extraction of brain MRI images [15].…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Fusion Approach to Detect Brain Tumor Using Machine Learning for MRI Images

Kaliannan¹,

Rengaraj²,

Daniel³

2022

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Medical Imaging challenges the recent researchers with variability of potential structures, positions and appearance strengths of various tumors present among the patients. The proposed work presents an effective brain tumor watershed segmentation technique created on 2D image followed by statistical feature extraction. Machine Learning models such as SVM, KNN, and XG boost were used to inspire the network design in order to extract tumor existence. The proposed segmentation algorithm has been tested and evaluated on original images that consist of an aggregate of 52 normal MRI volumes of distinctive patients with the presence of tumors or not signifying distinctive structures that obtains outcomes near to physical segmentation implementations. The novelty present in the proposed work classifies whether the tumor is present or not with an accuracy of approximately 98%.

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Section: Literature Reviewmentioning

confidence: 99%

A Novel Fusion Approach to Detect Brain Tumor Using Machine Learning for MRI Images

Kaliannan¹,

Rengaraj²,

Daniel³

2022

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“…For instance, human guards may become fatigued or fall asleep when viewing huge volumes of recordings or maintaining several footages, resulting in missed opportunities to discover uncommon criminal intention scenarios that may be caught in many footages. To solve this issue, pre-trained deep learning models may be used to eliminate the need for human interaction while identifying possible threats in public venues [11,34].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Models for Crime Intention Detection Using Object Detection

Hashi¹,

Abdirahman²,

Elmi³

et al. 2023

IJACSA

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The majority of visual based surveillance applications and security systems heavily rely on object detection, which serves as a critical module. In the context of crime scene analysis, images and videos play an essential role in capturing visual documentation of a particular scene. By detecting objects associated with a specific crime, police officers are able to reconstruct a scene for subsequent analysis. Nevertheless, the task of identifying objects of interest can be highly arduous for law enforcement agencies, mainly because of the massive amount of data that must be processed. Hence, the main objective of this paper is to propose a DL-based model for detecting tracked objects such as handheld firearms and informing the authority about the threat before the incident happens. We have applied VGG-19, ResNet, and GoogleNet as our deep learning models. The experiment result shows that ResNet50 has achieved the highest average accuracy of 0.92% compared to VGG19 and GoogleNet, which have achieved 0.91% and 0.89%, respectively. Also, YOLOv6 has achieved the highest MAP and inference speed compared to the faster R-CNN.

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A Comparative Study on the Identification of Informative Tweets Using Deep Neural Networks During Crisis

Ramya¹,

Christaline²

2022

Lecture Notes in Electrical Engineering

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Small Object Detection From Video and Classification Using Deep Learning

Cited by 6 publications

References 6 publications

A Novel Fusion Approach to Detect Brain Tumor Using Machine Learning for MRI Images

A Novel Fusion Approach to Detect Brain Tumor Using Machine Learning for MRI Images

Deep Learning Models for Crime Intention Detection Using Object Detection

A Comparative Study on the Identification of Informative Tweets Using Deep Neural Networks During Crisis

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