Browsing by Subject "Xception"
Now showing items 1-11 of 11
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CancerCare: A reliable and secured self-supervising and interactive system using deep learning
(Brac University, 2023-01)Cancer is the ultimate global health issue in the 21st century, as its burden is in creasing day by day. In the year 2020 [36], 18.1 million cancer cases were estimated, where 9.3 million were men and 8.8 million were ... -
Cassava leaf disease classification using deep learning and convolutional neural network ensemble
(Brac University, 2022-01)Cassava is a high-protein and nutrient-dense plant, notably inside the leaves. Cassava is often used as a rice alternative. Pests, viruses, bacteria, and fungus may cause a variety of illnesses on cassava leaves. This ... -
Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning
(Brac University, 2021-01)Retinal disease diagnosis by machine learning can be achieved using Deep Neural Network based predictors. Use of Explainable Artificial Intelligence (XAI) has the potential to explain the black box of those neural network ... -
A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
(Brac University, 2021-10)Depression and mental health issues (stress, nervousness, panic attacks, anxiety attacks etc.) are nowadays a major issue in the whole world. It is a common cause of mental illness that has been linked to an increased ... -
Deepfake detection in videos detecting face wrapping artifacts with convolutional neural network
(Brac University, 2021-01)Alteration of video les by changing the face of a person on frame is Deepfake. In such manipulated contents a person's face is used on a video performing or saying something that they never actually said or did. Deepfake ... -
Detection of skin diseases using deep learning
(2023-09)As a topic of global health importance, skin diseases must be quickly identified and accurately diagnosed to allow for effective treatment. Specifically for the classification of skin diseases, the use of deep learning ... -
Diabetic retinopathy detection and classification by using deep learning
(Brac University, 2022-01)Eyes are the most sensitive part of a human being and it is one of the most challenging tasks for a computer-aided system to classify its diseases. Many visionthreatening diseases such as, Glaucoma and Diabetic Retinopathy ... -
Early detection of diabetic retinopathy using deep learning techniques
(Brac University, 2021-10)We, humans, are the bearer of diseases. While most of them have a thoroughly researched and contemplated solution set, some of them do not. Diabetes is one of those common diseases that do not have a clear solution but ... -
Pest detection system using machine learning techniques
(Brac University, 2022-01)Countries like Bangladesh yield a significant portion of their economy from their agricultural sector. Agricultural pests, on the other hand, have a significant impact on both agricultural production and crop storage. ... -
Retinal Diseases Detection using Deep Learning
(Brac University, 2022-09)Retina is an important aspect of human vision because it converts light rays into images and sends messages to the brain. We run the danger of suffering long-term harm to the eyesight if we have a problem with our retina ... -
Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
(Brac University, 2022-01)Due to a number of reasons, marine ecosystems change with certain species of fish disappearing while novel species of fishes become a new staple within a given ecosystem, e.g., a lake, river, etc. Monitoring these changes ...
