Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision

Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Manylion Llyfryddiaeth
Prif Awduron:	Datta, Anurag, Fatema, Kaniz, Tasnim, Nowshin, Sitara, Faria, Das, Mrithik Kanti
Awduron Eraill:	Chakrabarty, Amitabha
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	Brac University 2022
Pynciau:	Human detection Social distancing YOLO algorithm Image processing Deep learning TensorFlow Computer vision MobileNet SSD Image processing > Digital techniques. Cognitive learning theory (Deep learning) Machine learning Human-machine systems
Mynediad Ar-lein:	http://hdl.handle.net/10361/17345

Eitemau Tebyg

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An efficient deep learning approach to detect skin Cancer
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An efficient ML approach to detect brain tumor using MRI images
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Corn leaf disease detection using deep convolution neural network
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Image processing and deep learning approach to evaluate earthquake resistance of urban buildings
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Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
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Automated overtaking assistance system: a real-time approach using deep learning techniques
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RetinalNet-500: a newly developed CNN model for eye disease detection
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A novel lightweight CNN approach for Bangladeshi sign language gesture recognition
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Damaged road detection using Image Processing and Deep Learning
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Real time dynamic facial recognition of subject at motion using angular image
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Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
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Application of CNN based architectures in detection of distracted drivers
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Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
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Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network
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Skin cancer detection and classification using multiple optimized deep convolutional neural network
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Analysis of deep learning models on low-light pest detection
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Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
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An active-learning based training-schedule for biomedical image segmentation on deep neural networks
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Transfer learning based industrial steel plates fault diagnosis using industrial fault signals
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An efficient deep learning approach to detect skin cancer using image data
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Cancer classification using deep learning from medical image data
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Multimodal approach to human detection in unconstrained environments using YOLOV7 for conventional, infrared & thermal cameras
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Protovision: utilizing prototypical networks for retinal diseases classification based on few-shot learning
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Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
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Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning
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Cyhoeddwyd: (2019)

Skin disease detection and classification using deep learning
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Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
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Exploring the applications of deep reinforcement learning and quantum variational circuit In quantum machine learning
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Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images
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An implementation and analysis of deep learning models for the detection of wheat diseases
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Cyhoeddwyd: (2024)

Real-time foul detection in football matches using machine learning techniques
gan: Siddiqui, Bishal Sadi, et al.
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Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
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Behavior change analysis due to violent video gaming using deep learning models
gan: Rahman, Akhlak Ur, et al.
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Empowering mobile network planning through deep learning: a path to democratization
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Structurally and semantically coherent deep image inpainting
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An interpretable transformer based approach to classify Malaria from blood cell images
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Real-time mastitis detection in livestock using deep learning and machine learning leveraging edge devices
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