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Found 8 papers, 1 papers with code
ConvoWaste: An Automatic Waste Segregation Machine Using Deep Learning
In this paper, deep learning and image processing techniques are applied to precisely classify the waste, and the detected waste is placed inside the corresponding bins with the help of a servo motor-based system.
convoHER2: A Deep Neural Network for Multi-Stage Classification of HER2 Breast Cancer
The outcomes of this study determined that the HER2 cancer detecting rates of the convoHER2 model are much enough to provide better diagnosis to the patient for recovering their HER2 breast cancer in future.
A comparative analysis of Graph Neural Networks and commonly used machine learning algorithms on fake news detection
Therefore, in this paper, we present a comparative analysis among some commonly used machine learning algorithms and Graph Neural Networks for detecting the spread of false news on social media platforms.
A Systematic Review on Interactive Virtual Reality Laboratory
Virtual Reality has become a significant element of education throughout the years.
A Deep Learning Framework to Reconstruct Face under Mask
This problem is complex because (i) it is difficult to determine the gender of an image hidden behind a mask, which causes the network to become confused and reconstruct the male face as a female or vice versa; (ii) we may receive images from multiple angles, making it extremely difficult to maintain the actual shape, topological structure of the face and a natural image; and (iii) there are problems with various mask forms because, in some cases, the area of the mask cannot be anticipated precisely; certain parts of the mask remain on the face after completion.
Approaches for Improving the Performance of Fake News Detection in Bangla: Imbalance Handling and Model Stacking
In this work, we present several strategies for resolving the imbalance issue for fake news detection in Bangla with a comparative assessment of proposed methodologies.
A Real-time Junk Food Recognition System based on Machine Learning
The goal was achieved using Convolution Neural Network (CNN) technology, which is well-known for image processing.
Image to Bengali Caption Generation Using Deep CNN and Bidirectional Gated Recurrent Unit
The purpose of this research is to propose a CNN and Bidirectional GRU based architecture model that generates natural language captions in the Bengali language from an image.
