UI development and functionality testing automation in android application

UI development and functionality testing automation in android application

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Xehetasun bibliografikoak
Egile Nagusiak:	Taus, Shehjad Ali, Hasan, Riazul, Rasul, Golam, Tabassum, Anila, Muttakin, Khondoker Al
Beste egile batzuk:	Alam, Md. Golam Rabiul
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Deep learning Natural language processing CNN RNN Computer-aided software engineering User interfaces (Computer systems) Deep learning (Machine learning)
Sarrera elektronikoa:	http://hdl.handle.net/10361/22853

Antzeko izenburuak

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Application of CNN based architectures in detection of distracted drivers
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A hybrid rumor detection model derived from a comparative study of supervised approaches
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An interpretable transformer based approach to classify Malaria from blood cell images
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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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Deep learning based predictive analytics for decentralized content caching in hierarchical edge networks
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Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
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Analysis of transformer and CNN based approaches for classifying renal abnormality from image data
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Plant leaf disease identification
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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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